CocoCaptions in PyTorch (1)

data └-coco |-imgs | |-train2014 | | |-COCO_train2014_000000000009.jpg | | |-COCO_train2014_000000000025.jpg | | |-COCO_train2014_000000000030.jpg | | ... | |-val2014/ | |-test2014/ | |-test2015/ | |-train2017/ | |-val2017/ | |-test2017/ | └-unlabeled2017/ └-anns |-trainval2014 | |-captions_train2014.json | |-instances_train2014.json | |-person_keypoints_train2014.json | |-captions_val2014.json | |-instances_val2014.json | └-person_keypoints_val2014.json |-test2014 | └-image_info_test2014.json |-test2015 | |-image_info_test2015.json | └-image_info_test-dev2015.json |-trainval2017 | |-captions_train2017.json | |-instances_train2017.json | |-person_keypoints_train2017.json | |-captions_val2017.json | |-instances_val2017.json | └-person_keypoints_val2017.json |-test2017 | |-image_info_test2017.json | └-image_info_test-dev2017.json |-stuff_trainval2017 | |-stuff_train2017.json | |-stuff_val2017.json | |-stuff_train2017_pixelmaps/ | | |-000000000009.png | | |-000000000025.png | | |-000000000030.png | | ... | |-stuff_val2017_pixelmaps/ | └-deprecated-challenge2017 | |-train-ids.txt | └-val-ids.txt |-panoptic_trainval2017 | |-panoptic_train2017.json | |-panoptic_val2017.json | |-panoptic_train2017/ | | |-000000000389.png | | |-000000000404.png | | |-000000000438.png | | ... | └-panoptic_val2017/ └-unlabeled2017 └-image_info_unlabeled2017.json 

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 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}:\n{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")