Module emblaze.thumbnails
Defines model classes to store thumbnail data in text and/or image formats.
Expand source code
"""
Defines model classes to store thumbnail data in text and/or image formats.
"""
import json
from typing import Text
import numpy as np
import pandas as pd
from io import BytesIO
from PIL import Image
import base64
import copy
from .datasets import ColumnarData
from .utils import Field, standardize_json
class Thumbnails:
"""
Defines a set of data suitable for displaying info about points visualized
in an embedding set.
"""
def __init__(self, thumbnail_format):
self.format = thumbnail_format
def to_json(self):
"""
Converts this set of thumbnails into a JSON object.
"""
return {
"format": self.format
}
@classmethod
def from_json(cls, data, ids=None):
"""
Loads this Thumbnails object from JSON. This base method chooses the
appropriate Thumbnails subclass to initialize, based on the format
declared in the given JSON object data. The ids parameter can be used
to subset the point IDs that are loaded from the file.
"""
if data["format"] == "spritesheet_and_text":
return CombinedThumbnails.from_json(data)
elif data["format"] == "spritesheet":
return ImageThumbnails.from_json(data, ids=ids)
elif data["format"] == "text_descriptions":
return TextThumbnails.from_json(data, ids=ids)
raise ValueError("Unsupported data format '{}'".format(data["format"]))
def get_ids(self):
"""Return a numpy array of the IDs used in this thumbnails object."""
raise NotImplementedError
def save(self, file_path_or_buffer):
"""
Save this Thumbnails object to the given file path or file-like object
(in JSON format).
"""
if isinstance(file_path_or_buffer, str):
# File path
with open(file_path_or_buffer, 'w') as file:
json.dump(self.to_json(), file)
else:
# File object
json.dump(self.to_json(), file_path_or_buffer)
@classmethod
def load(cls, file_path_or_buffer, ids=None):
"""
Load the appropriate Thumbnails subclass from the given file path or
file-like object containing JSON data.
"""
if isinstance(file_path_or_buffer, str):
# File path
with open(file_path_or_buffer, 'r') as file:
return cls.from_json(json.load(file), ids=ids)
else:
# File object
return cls.from_json(json.load(file_path_or_buffer), ids=ids)
class TextThumbnails(Thumbnails):
"""
Defines a set of textual thumbnails.
"""
def __init__(self, names, descriptions=None, ids=None):
"""
names: String values corresponding to a name for each point in the
dataset.
descriptions: Optional longer string descriptions for each point in the
dataset.
ids: If not None, a list of IDs that these thumbnails correspond to.
If not provided, the IDs are assumed to be zero-indexed ascending
integers.
"""
super().__init__("text_descriptions")
if ids is not None:
assert len(names) == len(ids), "Length mismatch: got {} names for {} IDs".format(len(names), len(ids))
if descriptions is not None:
assert len(descriptions) == len(ids), "Length mismatch: got {} descriptions for {} IDs".format(len(descriptions), len(ids))
self.data = ColumnarData({
Field.NAME: names
}, ids)
if descriptions is not None:
self.data.set_field(Field.DESCRIPTION, descriptions)
def get_ids(self):
return self.data.ids
def name(self, ids=None):
"""
Returns the name(s) for the given set of IDs, or all points if
ids is not provided.
"""
return self.data.field(Field.NAME, ids=ids)
def description(self, ids=None):
"""
Returns the description(s) for the given set of IDs, or all points if
ids is not provided. Returns None if descriptions are not present.
"""
return self.data.field(Field.DESCRIPTION, ids=ids)
def to_json(self):
result = super().to_json()
names = self.data.field(Field.NAME)
descriptions = self.data.field(Field.DESCRIPTION)
def _make_json_item(i, id_val):
item = {"id": id_val, "name": str(names[i])}
if descriptions is not None and descriptions[i]:
item["description"] = str(descriptions[i])
return item
result["items"] = {
id_val: _make_json_item(i, id_val)
for i, id_val in enumerate(self.data.ids)
if names[i] or (descriptions is not None and descriptions[i])
}
return standardize_json(result)
@classmethod
def from_json(cls, data, ids=None):
"""
Builds a TextThumbnails object from a JSON object. The provided object should
have an "items" key with a dictionary mapping ID values to text thumbnail
objects, each of which must have a 'name' and optionally 'description' keys.
"""
assert "items" in data, "JSON object must contain an 'items' field"
items = data["items"]
if ids is None:
try:
ids = [int(id_val) for id_val in list(items.keys())]
items = {int(k): v for k, v in items.items()}
except:
ids = list(items.keys())
ids = sorted(ids)
names = [items[id_val]["name"] for id_val in ids]
descriptions = [items[id_val].get("description", "") for id_val in ids]
return cls(names, descriptions, ids)
def __getitem__(self, ids):
"""
Returns text thumbnail information for the given IDs.
"""
if isinstance(ids, (list, np.ndarray, set)):
return [self[id_val] for id_val in ids]
else:
result = { "name": self.data.field(Field.NAME, ids) }
if self.data.has_field(Field.DESCRIPTION):
result["description"] = self.data.field(Field.DESCRIPTION, ids)
return result
MAX_IMAGE_DIM = 100
MAX_SPRITESHEET_DIM = 1000
class ImageThumbnails(Thumbnails):
"""
Defines a set of image thumbnails. All thumbnails are scaled to the same
dimensions to fit in a set of spritesheets.
"""
def __init__(self, images, spritesheets=None, ids=None, grid_dimensions=None, image_size=None, names=None, descriptions=None):
"""
Args:
images: An array of images, each represented as a numpy array. The
images contained can be different sizes if the images object is
provided as a list.
spritesheets: If provided, ignores the other spritesheet-generating
parameters and initializes the thumbnails object with previously
generated spritesheets.
ids: The IDs of the points to which each image belongs. If none, this
is assumed to be a zero-indexed increasing index.
grid_dimensions: Number of images per spritesheet, defined as
(images per row, images per column). If this is not provided,
it will be inferred to make the spritesheets a reasonable size.
image_size: Number of pixels per image, defined as (rows, cols).
If this is not defined, images will be resized to a maximum of
MAX_IMAGE_DIM x MAX_IMAGE_DIM, maintaining aspect ratio if all
images are the same size.
names: If provided, adds text names to each point. Names are assumed
to be in the same order as images.
descriptions: Similar to names, but these descriptions may be longer
and only show on the currently selected point(s).
"""
super().__init__("spritesheet")
if spritesheets is not None:
self.ids = ImageThumbnails._get_spritesheet_ids(spritesheets)
self.spritesheets = spritesheets
self.images = None
else:
self.images = images
self.ids = ids if ids is not None else np.arange(len(images))
self.make_spritesheets(images, self.ids, grid_dimensions, image_size)
self._id_index = {id: i for i, id in enumerate(self.ids)}
if names is not None:
self.text_data = ColumnarData({
Field.NAME: names
}, ids)
if descriptions is not None:
self.text_data.set_field(Field.DESCRIPTION, descriptions)
elif descriptions is not None:
self.text_data = ColumnarData({
Field.DESCRIPTION: descriptions
}, ids)
else:
self.text_data = None
def get_ids(self):
return self.ids
def __getitem__(self, ids):
"""
Returns image/text thumbnail information for the given IDs.
"""
if isinstance(ids, (list, np.ndarray, set)):
return [self[id_val] for id_val in ids]
else:
result = {}
result["image"] = self.image(ids)
if self.text_data is not None:
result["name"] = self.text_data.field(Field.NAME, ids)
if self.text_data.has_field(Field.DESCRIPTION):
result["description"] = self.text_data.field(Field.DESCRIPTION, ids)
return result
def image(self, ids=None):
"""
Returns the image(s) for the given ID or set of IDs, or all points if ids
is not provided.
"""
if self.images is None:
self.images = self._make_raw_images()
if isinstance(ids, (list, np.ndarray, set)):
index = [self._id_index.get(int(id_val), None) for id_val in ids]
return [self.images[i] if i is not None else None for i in index]
else:
index = self._id_index.get(int(ids), None)
if index is not None:
return self.images[index]
return None
def name(self, ids=None):
"""
Returns the name(s) for the given set of IDs, or all points if
ids is not provided. Returns None if names are not available.
"""
if self.text_data is None: return None
return self.text_data.field(Field.NAME, ids=ids)
def description(self, ids=None):
"""
Returns the description(s) for the given set of IDs, or all points if
ids is not provided. Returns None if descriptions are not present.
"""
if self.text_data is None: return None
return self.text_data.field(Field.DESCRIPTION, ids=ids)
def get_spritesheets(self):
return self.spritesheets
def to_json(self):
result = super().to_json()
result["spritesheets"] = self.spritesheets
if self.text_data is not None:
names = self.text_data.field(Field.NAME)
descriptions = self.text_data.field(Field.DESCRIPTION)
result["items"] = {
id_val: {
"id": id_val,
"name": str(names[i]) if names is not None else "",
"description": str(descriptions[i]) if descriptions is not None else "",
"frames": {} # Not implemented
} for i, id_val in enumerate(self.text_data.ids) if names[i] or descriptions[i]
}
return standardize_json(result)
@classmethod
def from_json(cls, data, ids=None):
"""
Builds an ImageThumbnails object from a JSON object. The provided object should
have a "spritesheets" object that defines PIXI spritesheets, and an
optional "items" key that contains text thumbnails (see TextThumbnails
for more information about the "items" field).
"""
assert "spritesheets" in data, "JSON object must contain a 'spritesheets' field"
spritesheets = data["spritesheets"]
if ids is None:
ids = cls._get_spritesheet_ids(spritesheets)
names = None
descriptions = None
if "items" in data:
items = data["items"]
names = [items[str(id_val)]["name"] for id_val in ids]
descriptions = [items[str(id_val)].get("description", "") for id_val in ids]
return cls(None,
spritesheets=spritesheets,
ids=ids,
names=names,
descriptions=descriptions)
@classmethod
def _get_spritesheet_ids(cls, spritesheets):
ids = sorted([k for sp in spritesheets.values() for k in sp["spec"]["frames"].keys()])
try:
ids = [int(id_val) for id_val in ids]
except:
pass
ids = sorted(ids)
return np.array(ids)
def _make_raw_images(self):
"""
Regenerates and returns the original images matrix based on self.spritesheets
and self.ids.
"""
assert len(self.spritesheets), "spritesheets is empty"
random_spec = self.spritesheets[list(self.spritesheets.keys())[0]]["spec"]["frames"]
random_frame = random_spec[list(random_spec.keys())[0]]["frame"]
cols = random_frame["w"]
rows = random_frame["h"]
result = np.zeros((len(self.ids), rows, cols, 4), dtype=np.uint8)
seen_ids = set()
for key, spritesheet in self.spritesheets.items():
buffer = BytesIO(base64.b64decode(spritesheet["image"].encode('ascii')))
img = np.array(Image.open(buffer, formats=('PNG',)))
for id_val, image_spec in spritesheet["spec"]["frames"].items():
frame = image_spec["frame"]
result[self._id_index[int(id_val)]] = img[frame["y"]:frame["y"] + frame["h"],
frame["x"]:frame["x"] + frame["w"]]
seen_ids.add(int(id_val))
if len(seen_ids & set(self.ids.tolist())) != len(self.ids):
print("missing ids when loading images from spritesheets:", set(self.ids.tolist()) - seen_ids)
return result
def make_spritesheets(self, images, ids, grid_dimensions=None, image_size=None):
"""
Generates a set of spritesheets from the given image data.
Args:
images: A matrix or list of images in RGBA format (e.g. shape = rows x cols x 4).
ids: The point IDs to associate with each image.
grid_dimensions: Number of images per spritesheet, defined as
(images per row, images per column)
image_size: Number of pixels per image, defined as (rows, cols)
"""
image_size = image_size or self._compute_image_size(images)
grid_dimensions = grid_dimensions or self._compute_grid_dimensions(image_size)
spritesheets = {}
current_spritesheet = None
current_image = None
image_index = 0
image_encoding_warning = False
assert len(ids) == len(images), "Number of IDs provided must be equal to number of images"
for i, id_val in enumerate(ids):
if i % (grid_dimensions[0] * grid_dimensions[1]) == 0:
if current_image is not None and current_spritesheet is not None:
img = Image.fromarray(current_image, 'RGBA')
with BytesIO() as output:
img.save(output, format='png')
contents = output.getvalue()
current_spritesheet["image"] = base64.b64encode(contents).decode('ascii')
current_spritesheet["imageFormat"] = "image/png"
image_index += 1
current_spritesheet = {
"spec": {
"meta": {
"image": "img_{}.png".format(image_index),
"size": {
"w": grid_dimensions[1] * image_size[1],
"h": grid_dimensions[0] * image_size[0]},
"format": "RGBA8888"
},
"frames": {}
}
}
spritesheets["img_{}.json".format(image_index)] = current_spritesheet
current_image = np.zeros((image_size[0] * grid_dimensions[0], image_size[1] * grid_dimensions[1], 4), dtype=np.uint8)
relative_i = i % (grid_dimensions[0] * grid_dimensions[1])
pos = (relative_i // grid_dimensions[1] * image_size[0], relative_i % grid_dimensions[1] * image_size[1])
# First validate the image
image = images[i]
assert len(image.shape) == 3, "Images must be 3-dimensional arrays (include a color channel)"
image = self._standardize_image_format(image, image.shape[:2])
if np.max(image[:,:,:3]) < 2 and not image_encoding_warning:
print("Warning: Your image pixel values are very small. ImageThumbnails uses integer pixel values from 0-255.")
image_encoding_warning = True
# Resize the image if necessary
if tuple(image.shape[:2]) != image_size:
resized_image = Image.fromarray(image).resize((image_size[1], image_size[0]))
image = np.array(resized_image)
assert image.shape == (*image_size, 4), "Incorrect resize shape! Something weird happened."
# Place the image
current_image[pos[0]:pos[0] + image_size[0], pos[1]:pos[1] + image_size[1],:] = image
current_spritesheet["spec"]["frames"][str(id_val)] = {
"frame": {
"x": pos[1],
"y": pos[0],
"w": image_size[1],
"h": image_size[0]
},
"rotated": False,
"trimmed": False
}
img = Image.fromarray(current_image, 'RGBA')
with BytesIO() as output:
img.save(output, format='png')
contents = output.getvalue()
current_spritesheet["image"] = base64.b64encode(contents).decode('ascii')
current_spritesheet["imageFormat"] = "image/png"
self.spritesheets = spritesheets
def _standardize_image_format(self, image, image_size):
"""
Converts the given image array to RGBA uint8 format.
Args:
image: An image matrix.
image_size: The size of the image in (rows, cols).
"""
image = image.astype(np.uint8)
result = np.zeros((image_size[0], image_size[1], 4), dtype=np.uint8)
if image.shape[2] == 1:
for channel in range(3):
result[:,:,channel] = image[:,:,0]
result[:,:,3] = 255
elif image.shape[2] == 3:
result[:,:,:3] = image
result[:,:,3] = 255
elif image.shape[2] == 4:
result = image
else:
raise ValueError("Incorrect image shape, expected 3rd dimension to be 1, 3 or 4; got {} instead".format(image.shape[2]))
return result
def _compute_image_size(self, images):
"""
Computes a reasonable image size to rescale all images to.
"""
if len(images) == 0: return (0, 0)
test_dim = images[0].shape[:2]
if all(img.shape[:2] == test_dim for img in images):
if max(*test_dim) < MAX_IMAGE_DIM:
# The images are already a reasonable size
return test_dim
# Resize preserving aspect ratio
scale = min(MAX_IMAGE_DIM / test_dim[0], MAX_IMAGE_DIM / test_dim[1])
return (int(test_dim[0] * scale), int(test_dim[1] * scale))
else:
# Get the average aspect ratio and choose a dimension so that no
# image is scaled up
aspect = np.mean([img.shape[0] / img.shape[1] for img in images])
if aspect < 1.0:
min_dim = min(MAX_IMAGE_DIM, np.min(np.array([img.shape[1] for img in images])))
return (int(min_dim * aspect), int(min_dim))
else:
min_dim = min(MAX_IMAGE_DIM, np.min(np.array([img.shape[0] for img in images])))
return (int(min_dim), int(min_dim / aspect))
def _compute_grid_dimensions(self, image_size):
"""
Computes a reasonable number of images per side of the spritesheet.
"""
return (MAX_SPRITESHEET_DIM // image_size[0], MAX_SPRITESHEET_DIM // image_size[1])
class CombinedThumbnails(Thumbnails):
"""
A class representing a combination of images and/or text thumbnails. The
thumbnail objects that are merged may have overlapping IDs, but they may not
have overlapping IDs for the same thumbnail type. For example, two
ImageThumbnails objects cannot both have images for the same point ID.
"""
def __init__(self, thumbnail_objects):
has_images = any(t.format == "spritesheet" for t in thumbnail_objects)
has_texts = any(t.format == "text_descriptions" for t in thumbnail_objects)
super().__init__(("spritesheet_and_text" if has_images else "text_descriptions") if has_texts else "spritesheet")
# Merge the list of representations together
self.ids = np.array(sorted(set.union(*(set(t.get_ids().tolist()) for t in thumbnail_objects))))
self._id_index = {id_val: i for i, id_val in enumerate(self.ids)}
names = None
descriptions = None
spritesheets = {}
seen_images = set()
seen_texts = set()
for t, thumbnails in enumerate(thumbnail_objects):
indexes = [self._id_index[id_val] for id_val in thumbnails.get_ids()]
if thumbnails.format == "spritesheet":
assert not set(thumbnails.get_ids().tolist()) & seen_images, "Overlapping image thumbnails"
for spritesheet_name, value in thumbnails.get_spritesheets().items():
new_spritesheet_name = str(t) + "_" + spritesheet_name
spritesheet = copy.deepcopy(value)
spritesheet["spec"]["meta"]["image"] = str(t) + "_" + spritesheet["spec"]["meta"]["image"]
spritesheets[new_spritesheet_name] = spritesheet
seen_images |= set(thumbnails.get_ids().tolist())
if thumbnails.format == "text_descriptions" or (thumbnails.format == "spritesheet" and thumbnails.name() is not None):
assert not set(thumbnails.get_ids().tolist()) & seen_texts, "Overlapping text thumbnails"
seen_texts |= set(thumbnails.get_ids().tolist())
nm = thumbnails.name()
if nm is not None:
if names is None: names = np.empty(len(self.ids), dtype='O')
names[indexes] = thumbnails.name()
desc = thumbnails.description()
if desc is not None:
if descriptions is None: descriptions = np.empty(len(self.ids), dtype='O')
descriptions[indexes] = desc
# Store an internal ImageThumbnails and a TextThumbnails object
self.image_thumbnails = ImageThumbnails(None, spritesheets=spritesheets) if spritesheets else None
self.text_thumbnails = TextThumbnails(names, descriptions, ids=self.ids) if names is not None else None
def get_ids(self):
return self.ids
def get_spritesheets(self):
return self.image_thumbnails.spritesheets if self.image_thumbnails else None
def to_json(self):
result = super().to_json()
if self.image_thumbnails is not None:
result["spritesheets"] = self.image_thumbnails.to_json()["spritesheets"]
if self.text_thumbnails is not None:
result["items"] = self.text_thumbnails.to_json()["items"]
return result
@classmethod
def from_json(cls, data, ids=None):
thumbnails = []
if "spritesheets" in data:
thumbnails.append(ImageThumbnails.from_json({"spritesheets": data["spritesheets"]}))
if "items" in data:
thumbnails.append(TextThumbnails.from_json({"items": data["items"]}))
return cls(thumbnails)
def image(self, ids=None):
"""
Returns the image(s) for the given ID or set of IDs, or all points if ids
is not provided.
"""
return self.image_thumbnails.image(ids=ids) if self.image_thumbnails else None
def name(self, ids=None):
"""
Returns the name(s) for the given set of IDs, or all points if
ids is not provided. Returns None if names are not available.
"""
return self.text_thumbnails.name(ids=ids) if self.text_thumbnails else None
def description(self, ids=None):
"""
Returns the description(s) for the given set of IDs, or all points if
ids is not provided. Returns None if descriptions are not present.
"""
return self.text_thumbnails.description(ids=ids) if self.text_thumbnails else None
Classes
class CombinedThumbnails (thumbnail_objects)-
A class representing a combination of images and/or text thumbnails. The thumbnail objects that are merged may have overlapping IDs, but they may not have overlapping IDs for the same thumbnail type. For example, two ImageThumbnails objects cannot both have images for the same point ID.
Expand source code
class CombinedThumbnails(Thumbnails): """ A class representing a combination of images and/or text thumbnails. The thumbnail objects that are merged may have overlapping IDs, but they may not have overlapping IDs for the same thumbnail type. For example, two ImageThumbnails objects cannot both have images for the same point ID. """ def __init__(self, thumbnail_objects): has_images = any(t.format == "spritesheet" for t in thumbnail_objects) has_texts = any(t.format == "text_descriptions" for t in thumbnail_objects) super().__init__(("spritesheet_and_text" if has_images else "text_descriptions") if has_texts else "spritesheet") # Merge the list of representations together self.ids = np.array(sorted(set.union(*(set(t.get_ids().tolist()) for t in thumbnail_objects)))) self._id_index = {id_val: i for i, id_val in enumerate(self.ids)} names = None descriptions = None spritesheets = {} seen_images = set() seen_texts = set() for t, thumbnails in enumerate(thumbnail_objects): indexes = [self._id_index[id_val] for id_val in thumbnails.get_ids()] if thumbnails.format == "spritesheet": assert not set(thumbnails.get_ids().tolist()) & seen_images, "Overlapping image thumbnails" for spritesheet_name, value in thumbnails.get_spritesheets().items(): new_spritesheet_name = str(t) + "_" + spritesheet_name spritesheet = copy.deepcopy(value) spritesheet["spec"]["meta"]["image"] = str(t) + "_" + spritesheet["spec"]["meta"]["image"] spritesheets[new_spritesheet_name] = spritesheet seen_images |= set(thumbnails.get_ids().tolist()) if thumbnails.format == "text_descriptions" or (thumbnails.format == "spritesheet" and thumbnails.name() is not None): assert not set(thumbnails.get_ids().tolist()) & seen_texts, "Overlapping text thumbnails" seen_texts |= set(thumbnails.get_ids().tolist()) nm = thumbnails.name() if nm is not None: if names is None: names = np.empty(len(self.ids), dtype='O') names[indexes] = thumbnails.name() desc = thumbnails.description() if desc is not None: if descriptions is None: descriptions = np.empty(len(self.ids), dtype='O') descriptions[indexes] = desc # Store an internal ImageThumbnails and a TextThumbnails object self.image_thumbnails = ImageThumbnails(None, spritesheets=spritesheets) if spritesheets else None self.text_thumbnails = TextThumbnails(names, descriptions, ids=self.ids) if names is not None else None def get_ids(self): return self.ids def get_spritesheets(self): return self.image_thumbnails.spritesheets if self.image_thumbnails else None def to_json(self): result = super().to_json() if self.image_thumbnails is not None: result["spritesheets"] = self.image_thumbnails.to_json()["spritesheets"] if self.text_thumbnails is not None: result["items"] = self.text_thumbnails.to_json()["items"] return result @classmethod def from_json(cls, data, ids=None): thumbnails = [] if "spritesheets" in data: thumbnails.append(ImageThumbnails.from_json({"spritesheets": data["spritesheets"]})) if "items" in data: thumbnails.append(TextThumbnails.from_json({"items": data["items"]})) return cls(thumbnails) def image(self, ids=None): """ Returns the image(s) for the given ID or set of IDs, or all points if ids is not provided. """ return self.image_thumbnails.image(ids=ids) if self.image_thumbnails else None def name(self, ids=None): """ Returns the name(s) for the given set of IDs, or all points if ids is not provided. Returns None if names are not available. """ return self.text_thumbnails.name(ids=ids) if self.text_thumbnails else None def description(self, ids=None): """ Returns the description(s) for the given set of IDs, or all points if ids is not provided. Returns None if descriptions are not present. """ return self.text_thumbnails.description(ids=ids) if self.text_thumbnails else NoneAncestors
Methods
def description(self, ids=None)-
Returns the description(s) for the given set of IDs, or all points if ids is not provided. Returns None if descriptions are not present.
Expand source code
def description(self, ids=None): """ Returns the description(s) for the given set of IDs, or all points if ids is not provided. Returns None if descriptions are not present. """ return self.text_thumbnails.description(ids=ids) if self.text_thumbnails else None def get_spritesheets(self)-
Expand source code
def get_spritesheets(self): return self.image_thumbnails.spritesheets if self.image_thumbnails else None def image(self, ids=None)-
Returns the image(s) for the given ID or set of IDs, or all points if ids is not provided.
Expand source code
def image(self, ids=None): """ Returns the image(s) for the given ID or set of IDs, or all points if ids is not provided. """ return self.image_thumbnails.image(ids=ids) if self.image_thumbnails else None def name(self, ids=None)-
Returns the name(s) for the given set of IDs, or all points if ids is not provided. Returns None if names are not available.
Expand source code
def name(self, ids=None): """ Returns the name(s) for the given set of IDs, or all points if ids is not provided. Returns None if names are not available. """ return self.text_thumbnails.name(ids=ids) if self.text_thumbnails else None
Inherited members
class ImageThumbnails (images, spritesheets=None, ids=None, grid_dimensions=None, image_size=None, names=None, descriptions=None)-
Defines a set of image thumbnails. All thumbnails are scaled to the same dimensions to fit in a set of spritesheets.
Args
images- An array of images, each represented as a numpy array. The images contained can be different sizes if the images object is provided as a list.
spritesheets- If provided, ignores the other spritesheet-generating parameters and initializes the thumbnails object with previously generated spritesheets.
ids- The IDs of the points to which each image belongs. If none, this is assumed to be a zero-indexed increasing index.
grid_dimensions- Number of images per spritesheet, defined as (images per row, images per column). If this is not provided, it will be inferred to make the spritesheets a reasonable size.
image_size- Number of pixels per image, defined as (rows, cols). If this is not defined, images will be resized to a maximum of MAX_IMAGE_DIM x MAX_IMAGE_DIM, maintaining aspect ratio if all images are the same size.
names- If provided, adds text names to each point. Names are assumed to be in the same order as images.
descriptions- Similar to names, but these descriptions may be longer and only show on the currently selected point(s).
Expand source code
class ImageThumbnails(Thumbnails): """ Defines a set of image thumbnails. All thumbnails are scaled to the same dimensions to fit in a set of spritesheets. """ def __init__(self, images, spritesheets=None, ids=None, grid_dimensions=None, image_size=None, names=None, descriptions=None): """ Args: images: An array of images, each represented as a numpy array. The images contained can be different sizes if the images object is provided as a list. spritesheets: If provided, ignores the other spritesheet-generating parameters and initializes the thumbnails object with previously generated spritesheets. ids: The IDs of the points to which each image belongs. If none, this is assumed to be a zero-indexed increasing index. grid_dimensions: Number of images per spritesheet, defined as (images per row, images per column). If this is not provided, it will be inferred to make the spritesheets a reasonable size. image_size: Number of pixels per image, defined as (rows, cols). If this is not defined, images will be resized to a maximum of MAX_IMAGE_DIM x MAX_IMAGE_DIM, maintaining aspect ratio if all images are the same size. names: If provided, adds text names to each point. Names are assumed to be in the same order as images. descriptions: Similar to names, but these descriptions may be longer and only show on the currently selected point(s). """ super().__init__("spritesheet") if spritesheets is not None: self.ids = ImageThumbnails._get_spritesheet_ids(spritesheets) self.spritesheets = spritesheets self.images = None else: self.images = images self.ids = ids if ids is not None else np.arange(len(images)) self.make_spritesheets(images, self.ids, grid_dimensions, image_size) self._id_index = {id: i for i, id in enumerate(self.ids)} if names is not None: self.text_data = ColumnarData({ Field.NAME: names }, ids) if descriptions is not None: self.text_data.set_field(Field.DESCRIPTION, descriptions) elif descriptions is not None: self.text_data = ColumnarData({ Field.DESCRIPTION: descriptions }, ids) else: self.text_data = None def get_ids(self): return self.ids def __getitem__(self, ids): """ Returns image/text thumbnail information for the given IDs. """ if isinstance(ids, (list, np.ndarray, set)): return [self[id_val] for id_val in ids] else: result = {} result["image"] = self.image(ids) if self.text_data is not None: result["name"] = self.text_data.field(Field.NAME, ids) if self.text_data.has_field(Field.DESCRIPTION): result["description"] = self.text_data.field(Field.DESCRIPTION, ids) return result def image(self, ids=None): """ Returns the image(s) for the given ID or set of IDs, or all points if ids is not provided. """ if self.images is None: self.images = self._make_raw_images() if isinstance(ids, (list, np.ndarray, set)): index = [self._id_index.get(int(id_val), None) for id_val in ids] return [self.images[i] if i is not None else None for i in index] else: index = self._id_index.get(int(ids), None) if index is not None: return self.images[index] return None def name(self, ids=None): """ Returns the name(s) for the given set of IDs, or all points if ids is not provided. Returns None if names are not available. """ if self.text_data is None: return None return self.text_data.field(Field.NAME, ids=ids) def description(self, ids=None): """ Returns the description(s) for the given set of IDs, or all points if ids is not provided. Returns None if descriptions are not present. """ if self.text_data is None: return None return self.text_data.field(Field.DESCRIPTION, ids=ids) def get_spritesheets(self): return self.spritesheets def to_json(self): result = super().to_json() result["spritesheets"] = self.spritesheets if self.text_data is not None: names = self.text_data.field(Field.NAME) descriptions = self.text_data.field(Field.DESCRIPTION) result["items"] = { id_val: { "id": id_val, "name": str(names[i]) if names is not None else "", "description": str(descriptions[i]) if descriptions is not None else "", "frames": {} # Not implemented } for i, id_val in enumerate(self.text_data.ids) if names[i] or descriptions[i] } return standardize_json(result) @classmethod def from_json(cls, data, ids=None): """ Builds an ImageThumbnails object from a JSON object. The provided object should have a "spritesheets" object that defines PIXI spritesheets, and an optional "items" key that contains text thumbnails (see TextThumbnails for more information about the "items" field). """ assert "spritesheets" in data, "JSON object must contain a 'spritesheets' field" spritesheets = data["spritesheets"] if ids is None: ids = cls._get_spritesheet_ids(spritesheets) names = None descriptions = None if "items" in data: items = data["items"] names = [items[str(id_val)]["name"] for id_val in ids] descriptions = [items[str(id_val)].get("description", "") for id_val in ids] return cls(None, spritesheets=spritesheets, ids=ids, names=names, descriptions=descriptions) @classmethod def _get_spritesheet_ids(cls, spritesheets): ids = sorted([k for sp in spritesheets.values() for k in sp["spec"]["frames"].keys()]) try: ids = [int(id_val) for id_val in ids] except: pass ids = sorted(ids) return np.array(ids) def _make_raw_images(self): """ Regenerates and returns the original images matrix based on self.spritesheets and self.ids. """ assert len(self.spritesheets), "spritesheets is empty" random_spec = self.spritesheets[list(self.spritesheets.keys())[0]]["spec"]["frames"] random_frame = random_spec[list(random_spec.keys())[0]]["frame"] cols = random_frame["w"] rows = random_frame["h"] result = np.zeros((len(self.ids), rows, cols, 4), dtype=np.uint8) seen_ids = set() for key, spritesheet in self.spritesheets.items(): buffer = BytesIO(base64.b64decode(spritesheet["image"].encode('ascii'))) img = np.array(Image.open(buffer, formats=('PNG',))) for id_val, image_spec in spritesheet["spec"]["frames"].items(): frame = image_spec["frame"] result[self._id_index[int(id_val)]] = img[frame["y"]:frame["y"] + frame["h"], frame["x"]:frame["x"] + frame["w"]] seen_ids.add(int(id_val)) if len(seen_ids & set(self.ids.tolist())) != len(self.ids): print("missing ids when loading images from spritesheets:", set(self.ids.tolist()) - seen_ids) return result def make_spritesheets(self, images, ids, grid_dimensions=None, image_size=None): """ Generates a set of spritesheets from the given image data. Args: images: A matrix or list of images in RGBA format (e.g. shape = rows x cols x 4). ids: The point IDs to associate with each image. grid_dimensions: Number of images per spritesheet, defined as (images per row, images per column) image_size: Number of pixels per image, defined as (rows, cols) """ image_size = image_size or self._compute_image_size(images) grid_dimensions = grid_dimensions or self._compute_grid_dimensions(image_size) spritesheets = {} current_spritesheet = None current_image = None image_index = 0 image_encoding_warning = False assert len(ids) == len(images), "Number of IDs provided must be equal to number of images" for i, id_val in enumerate(ids): if i % (grid_dimensions[0] * grid_dimensions[1]) == 0: if current_image is not None and current_spritesheet is not None: img = Image.fromarray(current_image, 'RGBA') with BytesIO() as output: img.save(output, format='png') contents = output.getvalue() current_spritesheet["image"] = base64.b64encode(contents).decode('ascii') current_spritesheet["imageFormat"] = "image/png" image_index += 1 current_spritesheet = { "spec": { "meta": { "image": "img_{}.png".format(image_index), "size": { "w": grid_dimensions[1] * image_size[1], "h": grid_dimensions[0] * image_size[0]}, "format": "RGBA8888" }, "frames": {} } } spritesheets["img_{}.json".format(image_index)] = current_spritesheet current_image = np.zeros((image_size[0] * grid_dimensions[0], image_size[1] * grid_dimensions[1], 4), dtype=np.uint8) relative_i = i % (grid_dimensions[0] * grid_dimensions[1]) pos = (relative_i // grid_dimensions[1] * image_size[0], relative_i % grid_dimensions[1] * image_size[1]) # First validate the image image = images[i] assert len(image.shape) == 3, "Images must be 3-dimensional arrays (include a color channel)" image = self._standardize_image_format(image, image.shape[:2]) if np.max(image[:,:,:3]) < 2 and not image_encoding_warning: print("Warning: Your image pixel values are very small. ImageThumbnails uses integer pixel values from 0-255.") image_encoding_warning = True # Resize the image if necessary if tuple(image.shape[:2]) != image_size: resized_image = Image.fromarray(image).resize((image_size[1], image_size[0])) image = np.array(resized_image) assert image.shape == (*image_size, 4), "Incorrect resize shape! Something weird happened." # Place the image current_image[pos[0]:pos[0] + image_size[0], pos[1]:pos[1] + image_size[1],:] = image current_spritesheet["spec"]["frames"][str(id_val)] = { "frame": { "x": pos[1], "y": pos[0], "w": image_size[1], "h": image_size[0] }, "rotated": False, "trimmed": False } img = Image.fromarray(current_image, 'RGBA') with BytesIO() as output: img.save(output, format='png') contents = output.getvalue() current_spritesheet["image"] = base64.b64encode(contents).decode('ascii') current_spritesheet["imageFormat"] = "image/png" self.spritesheets = spritesheets def _standardize_image_format(self, image, image_size): """ Converts the given image array to RGBA uint8 format. Args: image: An image matrix. image_size: The size of the image in (rows, cols). """ image = image.astype(np.uint8) result = np.zeros((image_size[0], image_size[1], 4), dtype=np.uint8) if image.shape[2] == 1: for channel in range(3): result[:,:,channel] = image[:,:,0] result[:,:,3] = 255 elif image.shape[2] == 3: result[:,:,:3] = image result[:,:,3] = 255 elif image.shape[2] == 4: result = image else: raise ValueError("Incorrect image shape, expected 3rd dimension to be 1, 3 or 4; got {} instead".format(image.shape[2])) return result def _compute_image_size(self, images): """ Computes a reasonable image size to rescale all images to. """ if len(images) == 0: return (0, 0) test_dim = images[0].shape[:2] if all(img.shape[:2] == test_dim for img in images): if max(*test_dim) < MAX_IMAGE_DIM: # The images are already a reasonable size return test_dim # Resize preserving aspect ratio scale = min(MAX_IMAGE_DIM / test_dim[0], MAX_IMAGE_DIM / test_dim[1]) return (int(test_dim[0] * scale), int(test_dim[1] * scale)) else: # Get the average aspect ratio and choose a dimension so that no # image is scaled up aspect = np.mean([img.shape[0] / img.shape[1] for img in images]) if aspect < 1.0: min_dim = min(MAX_IMAGE_DIM, np.min(np.array([img.shape[1] for img in images]))) return (int(min_dim * aspect), int(min_dim)) else: min_dim = min(MAX_IMAGE_DIM, np.min(np.array([img.shape[0] for img in images]))) return (int(min_dim), int(min_dim / aspect)) def _compute_grid_dimensions(self, image_size): """ Computes a reasonable number of images per side of the spritesheet. """ return (MAX_SPRITESHEET_DIM // image_size[0], MAX_SPRITESHEET_DIM // image_size[1])Ancestors
Static methods
def from_json(data, ids=None)-
Builds an ImageThumbnails object from a JSON object. The provided object should have a "spritesheets" object that defines PIXI spritesheets, and an optional "items" key that contains text thumbnails (see TextThumbnails for more information about the "items" field).
Expand source code
@classmethod def from_json(cls, data, ids=None): """ Builds an ImageThumbnails object from a JSON object. The provided object should have a "spritesheets" object that defines PIXI spritesheets, and an optional "items" key that contains text thumbnails (see TextThumbnails for more information about the "items" field). """ assert "spritesheets" in data, "JSON object must contain a 'spritesheets' field" spritesheets = data["spritesheets"] if ids is None: ids = cls._get_spritesheet_ids(spritesheets) names = None descriptions = None if "items" in data: items = data["items"] names = [items[str(id_val)]["name"] for id_val in ids] descriptions = [items[str(id_val)].get("description", "") for id_val in ids] return cls(None, spritesheets=spritesheets, ids=ids, names=names, descriptions=descriptions)
Methods
def description(self, ids=None)-
Returns the description(s) for the given set of IDs, or all points if ids is not provided. Returns None if descriptions are not present.
Expand source code
def description(self, ids=None): """ Returns the description(s) for the given set of IDs, or all points if ids is not provided. Returns None if descriptions are not present. """ if self.text_data is None: return None return self.text_data.field(Field.DESCRIPTION, ids=ids) def get_spritesheets(self)-
Expand source code
def get_spritesheets(self): return self.spritesheets def image(self, ids=None)-
Returns the image(s) for the given ID or set of IDs, or all points if ids is not provided.
Expand source code
def image(self, ids=None): """ Returns the image(s) for the given ID or set of IDs, or all points if ids is not provided. """ if self.images is None: self.images = self._make_raw_images() if isinstance(ids, (list, np.ndarray, set)): index = [self._id_index.get(int(id_val), None) for id_val in ids] return [self.images[i] if i is not None else None for i in index] else: index = self._id_index.get(int(ids), None) if index is not None: return self.images[index] return None def make_spritesheets(self, images, ids, grid_dimensions=None, image_size=None)-
Generates a set of spritesheets from the given image data.
Args
images- A matrix or list of images in RGBA format (e.g. shape = rows x cols x 4).
ids- The point IDs to associate with each image.
grid_dimensions- Number of images per spritesheet, defined as (images per row, images per column)
image_size- Number of pixels per image, defined as (rows, cols)
Expand source code
def make_spritesheets(self, images, ids, grid_dimensions=None, image_size=None): """ Generates a set of spritesheets from the given image data. Args: images: A matrix or list of images in RGBA format (e.g. shape = rows x cols x 4). ids: The point IDs to associate with each image. grid_dimensions: Number of images per spritesheet, defined as (images per row, images per column) image_size: Number of pixels per image, defined as (rows, cols) """ image_size = image_size or self._compute_image_size(images) grid_dimensions = grid_dimensions or self._compute_grid_dimensions(image_size) spritesheets = {} current_spritesheet = None current_image = None image_index = 0 image_encoding_warning = False assert len(ids) == len(images), "Number of IDs provided must be equal to number of images" for i, id_val in enumerate(ids): if i % (grid_dimensions[0] * grid_dimensions[1]) == 0: if current_image is not None and current_spritesheet is not None: img = Image.fromarray(current_image, 'RGBA') with BytesIO() as output: img.save(output, format='png') contents = output.getvalue() current_spritesheet["image"] = base64.b64encode(contents).decode('ascii') current_spritesheet["imageFormat"] = "image/png" image_index += 1 current_spritesheet = { "spec": { "meta": { "image": "img_{}.png".format(image_index), "size": { "w": grid_dimensions[1] * image_size[1], "h": grid_dimensions[0] * image_size[0]}, "format": "RGBA8888" }, "frames": {} } } spritesheets["img_{}.json".format(image_index)] = current_spritesheet current_image = np.zeros((image_size[0] * grid_dimensions[0], image_size[1] * grid_dimensions[1], 4), dtype=np.uint8) relative_i = i % (grid_dimensions[0] * grid_dimensions[1]) pos = (relative_i // grid_dimensions[1] * image_size[0], relative_i % grid_dimensions[1] * image_size[1]) # First validate the image image = images[i] assert len(image.shape) == 3, "Images must be 3-dimensional arrays (include a color channel)" image = self._standardize_image_format(image, image.shape[:2]) if np.max(image[:,:,:3]) < 2 and not image_encoding_warning: print("Warning: Your image pixel values are very small. ImageThumbnails uses integer pixel values from 0-255.") image_encoding_warning = True # Resize the image if necessary if tuple(image.shape[:2]) != image_size: resized_image = Image.fromarray(image).resize((image_size[1], image_size[0])) image = np.array(resized_image) assert image.shape == (*image_size, 4), "Incorrect resize shape! Something weird happened." # Place the image current_image[pos[0]:pos[0] + image_size[0], pos[1]:pos[1] + image_size[1],:] = image current_spritesheet["spec"]["frames"][str(id_val)] = { "frame": { "x": pos[1], "y": pos[0], "w": image_size[1], "h": image_size[0] }, "rotated": False, "trimmed": False } img = Image.fromarray(current_image, 'RGBA') with BytesIO() as output: img.save(output, format='png') contents = output.getvalue() current_spritesheet["image"] = base64.b64encode(contents).decode('ascii') current_spritesheet["imageFormat"] = "image/png" self.spritesheets = spritesheets def name(self, ids=None)-
Returns the name(s) for the given set of IDs, or all points if ids is not provided. Returns None if names are not available.
Expand source code
def name(self, ids=None): """ Returns the name(s) for the given set of IDs, or all points if ids is not provided. Returns None if names are not available. """ if self.text_data is None: return None return self.text_data.field(Field.NAME, ids=ids)
Inherited members
class TextThumbnails (names, descriptions=None, ids=None)-
Defines a set of textual thumbnails.
names: String values corresponding to a name for each point in the dataset. descriptions: Optional longer string descriptions for each point in the dataset. ids: If not None, a list of IDs that these thumbnails correspond to. If not provided, the IDs are assumed to be zero-indexed ascending integers.
Expand source code
class TextThumbnails(Thumbnails): """ Defines a set of textual thumbnails. """ def __init__(self, names, descriptions=None, ids=None): """ names: String values corresponding to a name for each point in the dataset. descriptions: Optional longer string descriptions for each point in the dataset. ids: If not None, a list of IDs that these thumbnails correspond to. If not provided, the IDs are assumed to be zero-indexed ascending integers. """ super().__init__("text_descriptions") if ids is not None: assert len(names) == len(ids), "Length mismatch: got {} names for {} IDs".format(len(names), len(ids)) if descriptions is not None: assert len(descriptions) == len(ids), "Length mismatch: got {} descriptions for {} IDs".format(len(descriptions), len(ids)) self.data = ColumnarData({ Field.NAME: names }, ids) if descriptions is not None: self.data.set_field(Field.DESCRIPTION, descriptions) def get_ids(self): return self.data.ids def name(self, ids=None): """ Returns the name(s) for the given set of IDs, or all points if ids is not provided. """ return self.data.field(Field.NAME, ids=ids) def description(self, ids=None): """ Returns the description(s) for the given set of IDs, or all points if ids is not provided. Returns None if descriptions are not present. """ return self.data.field(Field.DESCRIPTION, ids=ids) def to_json(self): result = super().to_json() names = self.data.field(Field.NAME) descriptions = self.data.field(Field.DESCRIPTION) def _make_json_item(i, id_val): item = {"id": id_val, "name": str(names[i])} if descriptions is not None and descriptions[i]: item["description"] = str(descriptions[i]) return item result["items"] = { id_val: _make_json_item(i, id_val) for i, id_val in enumerate(self.data.ids) if names[i] or (descriptions is not None and descriptions[i]) } return standardize_json(result) @classmethod def from_json(cls, data, ids=None): """ Builds a TextThumbnails object from a JSON object. The provided object should have an "items" key with a dictionary mapping ID values to text thumbnail objects, each of which must have a 'name' and optionally 'description' keys. """ assert "items" in data, "JSON object must contain an 'items' field" items = data["items"] if ids is None: try: ids = [int(id_val) for id_val in list(items.keys())] items = {int(k): v for k, v in items.items()} except: ids = list(items.keys()) ids = sorted(ids) names = [items[id_val]["name"] for id_val in ids] descriptions = [items[id_val].get("description", "") for id_val in ids] return cls(names, descriptions, ids) def __getitem__(self, ids): """ Returns text thumbnail information for the given IDs. """ if isinstance(ids, (list, np.ndarray, set)): return [self[id_val] for id_val in ids] else: result = { "name": self.data.field(Field.NAME, ids) } if self.data.has_field(Field.DESCRIPTION): result["description"] = self.data.field(Field.DESCRIPTION, ids) return resultAncestors
Static methods
def from_json(data, ids=None)-
Builds a TextThumbnails object from a JSON object. The provided object should have an "items" key with a dictionary mapping ID values to text thumbnail objects, each of which must have a 'name' and optionally 'description' keys.
Expand source code
@classmethod def from_json(cls, data, ids=None): """ Builds a TextThumbnails object from a JSON object. The provided object should have an "items" key with a dictionary mapping ID values to text thumbnail objects, each of which must have a 'name' and optionally 'description' keys. """ assert "items" in data, "JSON object must contain an 'items' field" items = data["items"] if ids is None: try: ids = [int(id_val) for id_val in list(items.keys())] items = {int(k): v for k, v in items.items()} except: ids = list(items.keys()) ids = sorted(ids) names = [items[id_val]["name"] for id_val in ids] descriptions = [items[id_val].get("description", "") for id_val in ids] return cls(names, descriptions, ids)
Methods
def description(self, ids=None)-
Returns the description(s) for the given set of IDs, or all points if ids is not provided. Returns None if descriptions are not present.
Expand source code
def description(self, ids=None): """ Returns the description(s) for the given set of IDs, or all points if ids is not provided. Returns None if descriptions are not present. """ return self.data.field(Field.DESCRIPTION, ids=ids) def name(self, ids=None)-
Returns the name(s) for the given set of IDs, or all points if ids is not provided.
Expand source code
def name(self, ids=None): """ Returns the name(s) for the given set of IDs, or all points if ids is not provided. """ return self.data.field(Field.NAME, ids=ids)
Inherited members
class Thumbnails (thumbnail_format)-
Defines a set of data suitable for displaying info about points visualized in an embedding set.
Expand source code
class Thumbnails: """ Defines a set of data suitable for displaying info about points visualized in an embedding set. """ def __init__(self, thumbnail_format): self.format = thumbnail_format def to_json(self): """ Converts this set of thumbnails into a JSON object. """ return { "format": self.format } @classmethod def from_json(cls, data, ids=None): """ Loads this Thumbnails object from JSON. This base method chooses the appropriate Thumbnails subclass to initialize, based on the format declared in the given JSON object data. The ids parameter can be used to subset the point IDs that are loaded from the file. """ if data["format"] == "spritesheet_and_text": return CombinedThumbnails.from_json(data) elif data["format"] == "spritesheet": return ImageThumbnails.from_json(data, ids=ids) elif data["format"] == "text_descriptions": return TextThumbnails.from_json(data, ids=ids) raise ValueError("Unsupported data format '{}'".format(data["format"])) def get_ids(self): """Return a numpy array of the IDs used in this thumbnails object.""" raise NotImplementedError def save(self, file_path_or_buffer): """ Save this Thumbnails object to the given file path or file-like object (in JSON format). """ if isinstance(file_path_or_buffer, str): # File path with open(file_path_or_buffer, 'w') as file: json.dump(self.to_json(), file) else: # File object json.dump(self.to_json(), file_path_or_buffer) @classmethod def load(cls, file_path_or_buffer, ids=None): """ Load the appropriate Thumbnails subclass from the given file path or file-like object containing JSON data. """ if isinstance(file_path_or_buffer, str): # File path with open(file_path_or_buffer, 'r') as file: return cls.from_json(json.load(file), ids=ids) else: # File object return cls.from_json(json.load(file_path_or_buffer), ids=ids)Subclasses
Static methods
def from_json(data, ids=None)-
Loads this Thumbnails object from JSON. This base method chooses the appropriate Thumbnails subclass to initialize, based on the format declared in the given JSON object data. The ids parameter can be used to subset the point IDs that are loaded from the file.
Expand source code
@classmethod def from_json(cls, data, ids=None): """ Loads this Thumbnails object from JSON. This base method chooses the appropriate Thumbnails subclass to initialize, based on the format declared in the given JSON object data. The ids parameter can be used to subset the point IDs that are loaded from the file. """ if data["format"] == "spritesheet_and_text": return CombinedThumbnails.from_json(data) elif data["format"] == "spritesheet": return ImageThumbnails.from_json(data, ids=ids) elif data["format"] == "text_descriptions": return TextThumbnails.from_json(data, ids=ids) raise ValueError("Unsupported data format '{}'".format(data["format"])) def load(file_path_or_buffer, ids=None)-
Load the appropriate Thumbnails subclass from the given file path or file-like object containing JSON data.
Expand source code
@classmethod def load(cls, file_path_or_buffer, ids=None): """ Load the appropriate Thumbnails subclass from the given file path or file-like object containing JSON data. """ if isinstance(file_path_or_buffer, str): # File path with open(file_path_or_buffer, 'r') as file: return cls.from_json(json.load(file), ids=ids) else: # File object return cls.from_json(json.load(file_path_or_buffer), ids=ids)
Methods
def get_ids(self)-
Return a numpy array of the IDs used in this thumbnails object.
Expand source code
def get_ids(self): """Return a numpy array of the IDs used in this thumbnails object.""" raise NotImplementedError def save(self, file_path_or_buffer)-
Save this Thumbnails object to the given file path or file-like object (in JSON format).
Expand source code
def save(self, file_path_or_buffer): """ Save this Thumbnails object to the given file path or file-like object (in JSON format). """ if isinstance(file_path_or_buffer, str): # File path with open(file_path_or_buffer, 'w') as file: json.dump(self.to_json(), file) else: # File object json.dump(self.to_json(), file_path_or_buffer) def to_json(self)-
Converts this set of thumbnails into a JSON object.
Expand source code
def to_json(self): """ Converts this set of thumbnails into a JSON object. """ return { "format": self.format }