PyTorch 中的 CocoCaptions (1)

from torchvision.datasets import CocoCaptions  cap_train2014_data = CocoCaptions(     root="data/coco/imgs/train2014",     annFile="data/coco/anns/trainval2014/captions_train2014.json" )  cap_train2014_data = CocoCaptions(     root="data/coco/imgs/train2014",     annFile="data/coco/anns/trainval2014/captions_train2014.json",     transform=None,     target_transform=None,     transforms=None )  ins_train2014_data = CocoCaptions(     root="data/coco/imgs/train2014",     annFile="data/coco/anns/trainval2014/instances_train2014.json" )  pk_train2014_data = CocoCaptions(     root="data/coco/imgs/train2014",     annFile="data/coco/anns/trainval2014/person_keypoints_train2014.json" )  len(cap_train2014_data), len(ins_train2014_data), len(pk_train2014_data) # (82783, 82783, 82783)  cap_val2014_data = CocoCaptions(     root="data/coco/imgs/val2014",     annFile="data/coco/anns/trainval2014/captions_val2014.json" )  ins_val2014_data = CocoCaptions(     root="data/coco/imgs/val2014",     annFile="data/coco/anns/trainval2014/instances_val2014.json" )  pk_val2014_data = CocoCaptions(     root="data/coco/imgs/val2014",     annFile="data/coco/anns/trainval2014/person_keypoints_val2014.json" )  len(cap_val2014_data), len(ins_val2014_data), len(pk_val2014_data) # (40504, 40504, 40504)  test2014_data = CocoCaptions(     root="data/coco/imgs/test2014",     annFile="data/coco/anns/test2014/image_info_test2014.json" )  test2015_data = CocoCaptions(     root="data/coco/imgs/test2015",     annFile="data/coco/anns/test2015/image_info_test2015.json" )  testdev2015_data = CocoCaptions(     root="data/coco/imgs/test2015",     annFile="data/coco/anns/test2015/image_info_test-dev2015.json" )  len(test2014_data), len(test2015_data), len(testdev2015_data) # (40775, 81434, 20288)  cap_train2014_data # Dataset CocoCaptions #     Number of datapoints: 82783 #     Root location: data/coco/imgs/train2014  cap_train2014_data.root # 'data/coco/imgs/train2014'  print(cap_train2014_data.transform) # None  print(cap_train2014_data.target_transform) # None  print(cap_train2014_data.transforms) # None  cap_train2014_data.coco # <pycocotools.coco.COCO at 0x759028ee1d00>  cap_train2014_data[26] # (<PIL.Image.Image image mode=RGB size=427x640>, #  ['three zeebras standing in a grassy field walking', #   'Three zebras are standing in an open field.', #   'Three zebra are walking through the grass of a field.', #   'Three zebras standing on a grassy dirt field.', #   'Three zebras grazing in green grass field area.'])  cap_train2014_data[179] # (<PIL.Image.Image image mode=RGB size=480x640>, #  ['a young guy walking in a forrest holding an object in his hand', #   'A partially black and white photo of a man throwing ... the woods.', #   'A disc golfer releases a throw from a dirt tee ... wooded course.', #   'The person is in the clearing of a wooded area. ', #   'a person throwing a frisbee at many trees '])  cap_train2014_data[194] # (<PIL.Image.Image image mode=RGB size=428x640>, #  ['A person on a court with a tennis racket.', #   'A man that is holding a racquet standing in the grass.', #   'A tennis player hits the ball during a match.', #   'The tennis player is poised to serve a ball.', #   'Man in white playing tennis on a court.'])  ins_train2014_data[26] # Error  ins_train2014_data[179] # Error  ins_train2014_data[194] # Error  pk_train2014_data[26] # (<PIL.Image.Image image mode=RGB size=427x640>, [])  pk_train2014_data[179] # Error  pk_train2014_data[194] # Error  cap_val2014_data[26] # (<PIL.Image.Image image mode=RGB size=640x360>, #  ['a close up of a child next to a cake with balloons', #   'A baby sitting in front of a cake wearing a tie.', #   'The young boy is dressed in a tie that matches his cake. ', #   'A child eating a birthday cake near some balloons.', #   'A baby eating a cake with a tie around ... the background.'])  cap_val2014_data[179] # (<PIL.Image.Image image mode=RGB size=500x302>, #  ['Many small children are posing together in the ... white photo. ', #   'A vintage school picture of grade school aged children.', #   'A black and white photo of a group of kids.', #   'A group of children standing next to each other.', #   'A group of children standing and sitting beside each other. '])  cap_val2014_data[194] # (<PIL.Image.Image image mode=RGB size=640x427>, #  ['A man hitting a tennis ball with a racquet.', #   'champion tennis player swats at the ball hoping to win', #   'A man is hitting his tennis ball with a recket on the court.', #   'a tennis player on a court with a racket', #   'A professional tennis player hits a ball as fans watch.'])  ins_val2014_data[26] # Error  ins_val2014_data[179] # Error  ins_val2014_data[194] # Error  pk_val2014_data[26] # Error  pk_val2014_data[179] # Error  pk_val2014_data[194] # Error  test2014_data[26] # (<PIL.Image.Image image mode=RGB size=640x640>, [])  test2014_data[179] # (<PIL.Image.Image image mode=RGB size=640x480>, [])  test2014_data[194] # (<PIL.Image.Image image mode=RGB size=640x360>, [])  test2015_data[26] # (<PIL.Image.Image image mode=RGB size=640x480>, [])  test2015_data[179] # (<PIL.Image.Image image mode=RGB size=640x426>, [])  test2015_data[194] # (<PIL.Image.Image image mode=RGB size=640x480>, [])  testdev2015_data[26] # (<PIL.Image.Image image mode=RGB size=640x360>, [])  testdev2015_data[179] # (<PIL.Image.Image image mode=RGB size=640x480>, [])  testdev2015_data[194] # (<PIL.Image.Image image mode=RGB size=640x480>, [])  import matplotlib.pyplot as plt from matplotlib.patches import Polygon, Rectangle import numpy as np from pycocotools import mask  def show_images(data, ims, main_title=None):     file = data.root.split('/')[-1]     fig, axes = plt.subplots(nrows=1, ncols=3, figsize=(14, 8))     fig.suptitle(t=main_title, y=0.9, fontsize=14)     x_crd = 0.02     for i, axis in zip(ims, axes.ravel()):         if data[i][1]:             im, anns = data[i]             axis.imshow(X=im)             y_crd = 0.0             for j, ann in enumerate(iterable=anns):                 text_list = ann.split()                 if len(text_list) > 9:                     text = " ".join(text_list[0:10]) + " ..."                 else:                     text = " ".join(text_list)                 plt.figtext(x=x_crd, y=y_crd, fontsize=10,                             s=f'{j} : {text}')                 y_crd -= 0.06             x_crd += 0.325             if i == 2 and file == "val2017":                 x_crd += 0.06         elif not data[i][1]:             im, _ = data[i]             axis.imshow(X=im)     fig.tight_layout()     plt.show()  ims = (26, 179, 194)  show_images(data=cap_train2014_data, ims=ims,              main_title="cap_train2014_data") show_images(data=cap_val2014_data, ims=ims,               main_title="cap_val2014_data") show_images(data=test2014_data, ims=ims,              main_title="test2014_data") show_images(data=test2015_data, ims=ims,              main_title="test2015_data") show_images(data=testdev2015_data, ims=ims,              main_title="testdev2015_data")