CocoCaptions in PyTorch (2)

from torchvision.datasets import CocoCaptions cap_train2017_data = CocoCaptions( root="data/coco/imgs/train2017", annFile="data/coco/anns/trainval2017/captions_train2017.json" ) ins_train2017_data = CocoCaptions( root="data/coco/imgs/train2017", annFile="data/coco/anns/trainval2017/instances_train2017.json" ) pk_train2017_data = CocoCaptions( root="data/coco/imgs/train2017", annFile="data/coco/anns/trainval2017/person_keypoints_train2017.json" ) len(cap_train2017_data), len(ins_train2017_data), len(pk_train2017_data) # (118287, 118287, 118287)  cap_val2017_data = CocoCaptions( root="data/coco/imgs/val2017", annFile="data/coco/anns/trainval2017/captions_val2017.json" ) ins_val2017_data = CocoCaptions( root="data/coco/imgs/val2017", annFile="data/coco/anns/trainval2017/instances_val2017.json" ) pk_val2017_data = CocoCaptions( root="data/coco/imgs/val2017", annFile="data/coco/anns/trainval2017/person_keypoints_val2017.json" ) len(cap_val2017_data), len(ins_val2017_data), len(pk_val2017_data) # (5000, 5000, 5000)  test2017_data = CocoCaptions( root="data/coco/imgs/test2017", annFile="data/coco/anns/test2017/image_info_test2017.json" ) testdev2017_data = CocoCaptions( root="data/coco/imgs/test2017", annFile="data/coco/anns/test2017/image_info_test-dev2017.json" ) len(test2017_data), len(testdev2017_data) # (40670, 20288)  cap_train2017_data[2] # (<PIL.Image.Image image mode=RGB size=640x428>, # ['A flower vase is sitting on a porch stand.', # 'White vase with different colored flowers sitting inside of it. ', # 'a white vase with many flowers on a stage', # 'A white vase filled with different colored flowers.', # 'A vase with red and white flowers outside on a sunny day.'])  cap_train2017_data[47] # (<PIL.Image.Image image mode=RGB size=640x427>, # ['A man standing in front of a microwave next to pots and pans.', # 'A man displaying pots and utensils on a wall.', # 'A man stands in a kitchen and motions towards pots and pans. ', # 'a man poses in front of some pots and pans ', # 'A man pointing to pots hanging from a pegboard on a gray wall.'])  cap_train2017_data[64] # (<PIL.Image.Image image mode=RGB size=480x640>, # ['A little girl holding wet broccoli in her hand. ', # 'The young child is happily holding a fresh vegetable. ', # 'A little girl holds a hand full of wet broccoli. ', # 'A little girl holds a piece of broccoli towards the camera.', # 'a small kid holds on to some vegetables '])  ins_train2017_data[2] # Error  ins_train2017_data[47] # Error  ins_train2017_data[67] # Error  pk_train2017_data[2] # (<PIL.Image.Image image mode=RGB size=640x428>, [])  pk_train2017_data[47] # Error  pk_train2017_data[64] # Error  cap_val2017_data[2] # (<PIL.Image.Image image mode=RGB size=640x483>, # ['Bedroom scene with a bookcase, blue comforter and window.', # 'A bedroom with a bookshelf full of books.', # 'This room has a bed with blue sheets and a large bookcase', # 'A bed and a mirror in a small room.', # 'a bed room with a neatly made bed a window and a book shelf'])  cap_val2017_data[47] # (<PIL.Image.Image image mode=RGB size=640x480>, # ['A group of people cutting a ribbon on a street.', # 'A man uses a pair of big scissors to cut a pink ribbon.', # 'A man cutting a ribbon at a ceremony ', # 'A group of people on the sidewalk watching two young children.', # 'A group of people holding a large pair of scissors to a ribbon.'])  cap_val2017_data[64] # (<PIL.Image.Image image mode=RGB size=375x500>, # ['A man and a women posing next to one another in front of a table.', # 'A man and woman hugging in a restaurant', # 'A man and woman standing next to a table.', # 'A happy man and woman pose for a picture.', # 'A man and woman posing for a picture in a sports bar.'])  ins_val2017_data[2] # Error  ins_val2017_data[47] # Error  ins_val2017_data[64] # Error  pk_val2017_data[2] # (<PIL.Image.Image image mode=RGB size=640x483>, [])  pk_val2017_data[47] # Error  pk_val2017_data[64] # Error  test2017_data[2] # (<PIL.Image.Image image mode=RGB size=640x427>, [])  test2017_data[47] # (<PIL.Image.Image image mode=RGB size=640x406>, [])  test2017_data[64] # (<PIL.Image.Image image mode=RGB size=640x427>, [])  testdev2017_data[2] # (<PIL.Image.Image image mode=RGB size=640x427>, [])  testdev2017_data[47] # (<PIL.Image.Image image mode=RGB size=480x640>, [])  testdev2017_data[64] # (<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 = (2, 47, 64) show_images(data=cap_train2017_data, ims=ims, main_title="cap_train2017_data") show_images(data=cap_val2017_data, ims=ims, main_title="cap_val2017_data") show_images(data=test2017_data, ims=ims, main_title="test2017_data") show_images(data=testdev2017_data, ims=ims, main_title="testdev2017_data")