PyTorch 中的 CocoCaptions (2)

from torchvision.datasets import CocoCaptionscap_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] # Errorins_train2017_data[47] # Errorins_train2017_data[67] # Errorpk_train2017_data[2]# (<PIL.Image.Image image mode=RGB size=640x428>, [])pk_train2017_data[47] # Errorpk_train2017_data[64] # Errorcap_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] # Errorins_val2017_data[47] # Errorins_val2017_data[64] # Errorpk_val2017_data[2]# (<PIL.Image.Image image mode=RGB size=640x483>, [])pk_val2017_data[47] # Errorpk_val2017_data[64] # Errortest2017_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 pltdef 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 = (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")