PyTorch 中的 CocoCaptions (1)

from torchvision.datasets import CocoCaptionscap_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/train2014cap_train2014_data.root# 'data/coco/imgs/train2014'print(cap_train2014_data.transform)# Noneprint(cap_train2014_data.target_transform)# Noneprint(cap_train2014_data.transforms)# Nonecap_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] # Errorins_train2014_data[179] # Errorins_train2014_data[194] # Errorpk_train2014_data[26]# (<PIL.Image.Image image mode=RGB size=427x640>, [])pk_train2014_data[179] # Errorpk_train2014_data[194] # Errorcap_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] # Errorins_val2014_data[179] # Errorins_val2014_data[194] # Errorpk_val2014_data[26] # Errorpk_val2014_data[179] # Errorpk_val2014_data[194] # Errortest2014_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 pltfrom matplotlib.patches import Polygon, Rectangleimport numpy as npfrom pycocotools import maskdef 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")