FileNotFoundError("No such file: '%s'" % fn)

[Mstfakts]

Hello all,

I try to train Mask-RCNN via COCO-2017 key-point dataset. However, I got an error that I could not understand/overcome it. I work on Colab, so I uploaded coco2017 dataset to google drive, and every time I mount it to the colab. Anyway, This is dataset directory:
"/content/drive/My Drive/cocodataset/"
There r 2 files in cocodataset: annotations, train2017, val2017 (I have not uploaded test yet.)

Here is an error message:

Train heads

Starting at epoch 0. LR=0.002

Checkpoint Path: /content/drive/My Drive/Keypoints-of-humanpose-with-Mask-R-CNN-master/logs/coco20200503T1902/mask_rcnn_coco_{epoch:04d}.h5
Selecting layers to train
fpn_c5p5 (Conv2D)
fpn_c4p4 (Conv2D)
fpn_c3p3 (Conv2D)
fpn_c2p2 (Conv2D)
fpn_p5 (Conv2D)
fpn_p2 (Conv2D)
fpn_p3 (Conv2D)
fpn_p4 (Conv2D)
In model: rpn_model
rpn_conv_shared (Conv2D)
rpn_class_raw (Conv2D)
rpn_bbox_pred (Conv2D)
mrcnn_keypoint_mask_conv1 (TimeDistributed)
mrcnn_keypoint_mask_bn1 (TimeDistributed)
mrcnn_keypoint_mask_conv2 (TimeDistributed)
mrcnn_keypoint_mask_bn2 (TimeDistributed)
mrcnn_keypoint_mask_conv3 (TimeDistributed)
mrcnn_keypoint_mask_bn3 (TimeDistributed)
mrcnn_keypoint_mask_conv4 (TimeDistributed)
mrcnn_keypoint_mask_bn4 (TimeDistributed)
mrcnn_keypoint_mask_conv5 (TimeDistributed)
mrcnn_keypoint_mask_bn5 (TimeDistributed)
mrcnn_keypoint_mask_conv6 (TimeDistributed)
mrcnn_mask_conv1 (TimeDistributed)
mrcnn_keypoint_mask_bn6 (TimeDistributed)
mrcnn_mask_bn1 (TimeDistributed)
mrcnn_keypoint_mask_conv7 (TimeDistributed)
mrcnn_mask_conv2 (TimeDistributed)
mrcnn_keypoint_mask_bn7 (TimeDistributed)
mrcnn_mask_bn2 (TimeDistributed)
mrcnn_class_conv1 (TimeDistributed)
mrcnn_class_bn1 (TimeDistributed)
mrcnn_keypoint_mask_conv8 (TimeDistributed)
mrcnn_mask_conv3 (TimeDistributed)
mrcnn_keypoint_mask_bn8 (TimeDistributed)
mrcnn_mask_bn3 (TimeDistributed)
mrcnn_class_conv2 (TimeDistributed)
mrcnn_class_bn2 (TimeDistributed)
mrcnn_keypoint_mask_deconv (TimeDistributed)
mrcnn_mask_conv4 (TimeDistributed)
mrcnn_mask_bn4 (TimeDistributed)
mrcnn_bbox_fc (TimeDistributed)
mrcnn_mask_deconv (TimeDistributed)
mrcnn_class_logits (TimeDistributed)
mrcnn_mask (TimeDistributed)
/tensorflow-1.15.2/python3.6/tensorflow_core/python/framework/indexed_slices.py:424: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of memory.
"Converting sparse IndexedSlices to a dense Tensor of unknown shape. "
/tensorflow-1.15.2/python3.6/tensorflow_core/python/framework/indexed_slices.py:424: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of memory.
"Converting sparse IndexedSlices to a dense Tensor of unknown shape. "
/tensorflow-1.15.2/python3.6/tensorflow_core/python/framework/indexed_slices.py:424: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of memory.
"Converting sparse IndexedSlices to a dense Tensor of unknown shape. "
/tensorflow-1.15.2/python3.6/tensorflow_core/python/framework/indexed_slices.py:424: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of memory.
"Converting sparse IndexedSlices to a dense Tensor of unknown shape. "
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/backend/tensorflow_backend.py:422: The name tf.global_variables is deprecated. Please use tf.compat.v1.global_variables instead.

WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/callbacks/tensorboard_v1.py:200: The name tf.summary.merge_all is deprecated. Please use tf.compat.v1.summary.merge_all instead.

WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/keras/callbacks/tensorboard_v1.py:203: The name tf.summary.FileWriter is deprecated. Please use tf.compat.v1.summary.FileWriter instead.

/usr/local/lib/python3.6/dist-packages/keras/engine/training_generator.py:49: UserWarning: Using a generator with use_multiprocessing=True and multiple workers may duplicate your data. Please consider using the keras.utils.Sequence class. UserWarning('Using a generator with use_multiprocessing=True`'
Epoch 1/15
/usr/local/lib/python3.6/dist-packages/keras/utils/data_utils.py:718: UserWarning: An input could not be retrieved. It could be because a worker has died.We do not have any information on the lost sample.
UserWarning)
ERROR:root:Error processing image {'id': 267417, 'source': 'coco', 'path': '/content/drive/My Drive/cocodataset//train2017/000000267417.jpg', 'width': 640, 'height': 360, 'annotations': [{'segmentation': [[273.63, 163.05, 280.09, 129.15, 304.3, 117.04, 322.87, 134.8, 343.05, 155.78, 358.39, 213.09, 393.9, 221.97, 387.44, 250.22, 374.53, 232.47, 343.86, 240.54, 330.13, 255.07, 309.96, 259.91, 240.54, 253.45, 238.92, 234.89, 274.44, 223.59]], 'num_keypoints': 16, 'area': 10970.8016, 'iscrowd': 0, 'keypoints': [289, 164, 2, 297, 159, 2, 284, 157, 2, 314, 155, 2, 0, 0, 0, 326, 166, 2, 281, 175, 2, 350, 210, 2, 279, 216, 2, 315, 226, 2, 284, 229, 2, 330, 227, 2, 295, 229, 2, 383, 230, 2, 248, 240, 2, 314, 250, 2, 316, 255, 2], 'image_id': 267417, 'bbox': [238.92, 117.04, 154.98, 142.87], 'category_id': 1, 'id': 481757}, {'segmentation': [[366.51, 124.45, 370.47, 124.68, 372.33, 127.25, 373.26, 133.76, 373.26, 137.02, 373.26, 140.52, 372.57, 148.2, 368.14, 150.76, 363.25, 151.69, 360.92, 151, 359.06, 149.37, 358.59, 149.37, 357.66, 151.46, 351.84, 160.54, 347.42, 165.2, 345.79, 162.4, 346.02, 155.19, 349.05, 150.06, 352.31, 142.85, 353.24, 140.05, 356.73, 139.35, 359.76, 139.35, 361.39, 139.12, 364.42, 134.23, 364.65, 133.53, 363.02, 130.27, 364.18, 126.08]], 'num_keypoints': 0, 'area': 474.04425, 'iscrowd': 0, 'keypoints': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'image_id': 267417, 'bbox': [345.79, 124.45, 27.47, 40.75], 'category_id': 1, 'id': 492854}, {'segmentation': [[199.17, 268.36, 174.86, 260.88, 158.96, 253.4, 146.81, 257.14, 135.58, 257.14, 140.26, 246.86, 133.71, 221.61, 163.64, 174.86, 165.51, 155.22, 167.38, 144, 184.21, 132.78, 206.65, 137.45, 212.26, 157.09, 213.19, 172.05, 216.94, 177.66, 234.7, 189.82, 239.38, 196.36, 228.16, 216.94, 234.7, 233.77, 225.35, 237.51, 227.22, 251.53, 227.22, 256.21, 220.68, 260.88, 215.06, 270.23, 198.23, 270.23]], 'num_keypoints': 17, 'area': 9249.96205, 'iscrowd': 0, 'keypoints': [188, 177, 2, 195, 172, 2, 182, 170, 2, 206, 169, 2, 170, 167, 2, 202, 184, 2, 162, 188, 2, 232, 197, 2, 144, 220, 2, 222, 211, 2, 145, 245, 2, 198, 238, 2, 174, 243, 2, 218, 209, 2, 211, 261, 2, 217, 251, 2, 172, 258, 2], 'image_id': 267417, 'bbox': [133.71, 132.78, 105.67, 137.45], 'category_id': 1, 'id': 2154683}, {'segmentation': [[334.74, 146.64, 334.74, 144.83, 335.42, 141.89, 335.87, 140.08, 336.55, 136.01, 337.91, 134.88, 339.72, 133.52, 342.43, 131.94, 342.43, 128.99, 344.02, 125.38, 345.83, 123.34, 347.86, 123.57, 350.35, 126.05, 351.03, 127.64, 347.86, 132.16, 351.93, 134.65, 352.16, 140.3, 352.16, 142.79, 349.9, 148.22, 347.64, 150.48, 346.05, 153.42, 345.6, 156.59, 341.3, 155.23, 338.36, 150.03]], 'num_keypoints': 0, 'area': 354.4833, 'iscrowd': 0, 'keypoints': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'image_id': 267417, 'bbox': [334.74, 123.34, 17.42, 33.25], 'category_id': 1, 'id': 2161890}]}
Traceback (most recent call last):
File "/content/drive/My Drive/Keypoints-of-humanpose-with-Mask-R-CNN-master/model.py", line 2194, in data_generator_keypoint
load_image_gt_keypoints(dataset, config, image_id, augment, use_mini_mask=config.USE_MINI_MASK)
File "/content/drive/My Drive/Keypoints-of-humanpose-with-Mask-R-CNN-master/model.py", line 1732, in load_image_gt_keypoints
image = dataset.load_image(image_id)
File "/content/drive/My Drive/Keypoints-of-humanpose-with-Mask-R-CNN-master/utils.py", line 418, in load_image
image = skimage.io.imread(self.image_info[image_id]['path'])
File "/usr/local/lib/python3.6/dist-packages/skimage/io/_io.py", line 48, in imread
img = call_plugin('imread', fname, plugin=plugin, **plugin_args)
File "/usr/local/lib/python3.6/dist-packages/skimage/io/manage_plugins.py", line 210, in call_plugin
return func(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/skimage/io/_plugins/imageio_plugin.py", line 10, in imread
return np.asarray(imageio_imread(*args, **kwargs))
File "/usr/local/lib/python3.6/dist-packages/imageio/core/functions.py", line 221, in imread
reader = read(uri, format, "i", **kwargs)
File "/usr/local/lib/python3.6/dist-packages/imageio/core/functions.py", line 130, in get_reader
request = Request(uri, "r" + mode, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/imageio/core/request.py", line 125, in init
self._parse_uri(uri)
File "/usr/local/lib/python3.6/dist-packages/imageio/core/request.py", line 273, in _parse_uri
raise FileNotFoundError("No such file: '%s'" % fn)
FileNotFoundError: No such file: '/content/drive/My Drive/cocodataset/train2017/000000267417.jpg'
ERROR:root:Error processing image {'id': 267417, 'source': 'coco', 'path': '/content/drive/My Drive/cocodataset//train2017/000000267417.jpg', 'width': 640, 'height': 360, 'annotations': [{'segmentation': [[273.63, 163.05, 280.09, 129.15, 304.3, 117.04, 322.87, 134.8, 343.05, 155.78, 358.39, 213.09, 393.9, 221.97, 387.44, 250.22, 374.53, 232.47, 343.86, 240.54, 330.13, 255.07, 309.96, 259.91, 240.54, 253.45, 238.92, 234.89, 274.44, 223.59]], 'num_keypoints': 16, 'area': 10970.8016, 'iscrowd': 0, 'keypoints': [289, 164, 2, 297, 159, 2, 284, 157, 2, 314, 155, 2, 0, 0, 0, 326, 166, 2, 281, 175, 2, 350, 210, 2, 279, 216, 2, 315, 226, 2, 284, 229, 2, 330, 227, 2, 295, 229, 2, 383, 230, 2, 248, 240, 2, 314, 250, 2, 316, 255, 2], 'image_id': 267417, 'bbox': [238.92, 117.04, 154.98, 142.87], 'category_id': 1, 'id': 481757}, {'segmentation': [[366.51, 124.45, 370.47, 124.68, 372.33, 127.25, 373.26, 133.76, 373.26, 137.02, 373.26, 140.52, 372.57, 148.2, 368.14, 150.76, 363.25, 151.69, 360.92, 151, 359.06, 149.37, 358.59, 149.37, 357.66, 151.46, 351.84, 160.54, 347.42, 165.2, 345.79, 162.4, 346.02, 155.19, 349.05, 150.06, 352.31, 142.85, 353.24, 140.05, 356.73, 139.35, 359.76, 139.35, 361.39, 139.12, 364.42, 134.23, 364.65, 133.53, 363.02, 130.27, 364.18, 126.08]], 'num_keypoints': 0, 'area': 474.04425, 'iscrowd': 0, 'keypoints': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'image_id': 267417, 'bbox': [345.79, 124.45, 27.47, 40.75], 'category_id': 1, 'id': 492854}, {'segmentation': [[199.17, 268.36, 174.86, 260.88, 158.96, 253.4, 146.81, 257.14, 135.58, 257.14, 140.26, 246.86, 133.71, 221.61, 163.64, 174.86, 165.51, 155.22, 167.38, 144, 184.21, 132.78, 206.65, 137.45, 212.26, 157.09, 213.19, 172.05, 216.94, 177.66, 234.7, 189.82, 239.38, 196.36, 228.16, 216.94, 234.7, 233.77, 225.35, 237.51, 227.22, 251.53, 227.22, 256.21, 220.68, 260.88, 215.06, 270.23, 198.23, 270.23]], 'num_keypoints': 17, 'area': 9249.96205, 'iscrowd': 0, 'keypoints': [188, 177, 2, 195, 172, 2, 182, 170, 2, 206, 169, 2, 170, 167, 2, 202, 184, 2, 162, 188, 2, 232, 197, 2, 144, 220, 2, 222, 211, 2, 145, 245, 2, 198, 238, 2, 174, 243, 2, 218, 209, 2, 211, 261, 2, 217, 251, 2, 172, 258, 2], 'image_id': 267417, 'bbox': [133.71, 132.78, 105.67, 137.45], 'category_id': 1, 'id': 2154683}, {'segmentation': [[334.74, 146.64, 334.74, 144.83, 335.42, 141.89, 335.87, 140.08, 336.55, 136.01, 337.91, 134.88, 339.72, 133.52, 342.43, 131.94, 342.43, 128.99, 344.02, 125.38, 345.83, 123.34, 347.86, 123.57, 350.35, 126.05, 351.03, 127.64, 347.86, 132.16, 351.93, 134.65, 352.16, 140.3, 352.16, 142.79, 349.9, 148.22, 347.64, 150.48, 346.05, 153.42, 345.6, 156.59, 341.3, 155.23, 338.36, 150.03]], 'num_keypoints': 0, 'area': 354.4833, 'iscrowd': 0, 'keypoints': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'image_id': 267417, 'bbox': [334.74, 123.34, 17.42, 33.25], 'category_id': 1, 'id': 2161890}]}
Traceback (most recent call last):
File "/content/drive/My Drive/Keypoints-of-humanpose-with-Mask-R-CNN-master/model.py", line 2194, in data_generator_keypoint
load_image_gt_keypoints(dataset, config, image_id, augment, use_mini_mask=config.USE_MINI_MASK)
File "/content/drive/My Drive/Keypoints-of-humanpose-with-Mask-R-CNN-master/model.py", line 1732, in load_image_gt_keypoints
image = dataset.load_image(image_id)
File "/content/drive/My Drive/Keypoints-of-humanpose-with-Mask-R-CNN-master/utils.py", line 418, in load_image
image = skimage.io.imread(self.image_info[image_id]['path'])
File "/usr/local/lib/python3.6/dist-packages/skimage/io/_io.py", line 48, in imread
img = call_plugin('imread', fname, plugin=plugin, **plugin_args)
File "/usr/local/lib/python3.6/dist-packages/skimage/io/manage_plugins.py", line 210, in call_plugin
return func(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/skimage/io/_plugins/imageio_plugin.py", line 10, in imread
return np.asarray(imageio_imread(*args, **kwargs))
File "/usr/local/lib/python3.6/dist-packages/imageio/core/functions.py", line 221, in imread
reader = read(uri, format, "i", **kwargs)
File "/usr/local/lib/python3.6/dist-packages/imageio/core/functions.py", line 130, in get_reader
request = Request(uri, "r" + mode, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/imageio/core/request.py", line 125, in init
self._parse_uri(uri)
File "/usr/local/lib/python3.6/dist-packages/imageio/core/request.py", line 273, in _parse_uri
raise FileNotFoundError("No such file: '%s'" % fn)
FileNotFoundError: No such file: '/content/drive/My Drive/cocodataset/train2017/000000267417.jpg'
ERROR:root:Error processing image {'id': 574497, 'source': 'coco', 'path': '/content/drive/My Drive/cocodataset//train2017/000000574497.jpg', 'width': 640, 'height': 418, 'annotations': [{'segmentation': [[238.82, 264.66, 239.33, 242.01, 243.35, 240.5, 242.85, 226.41, 250.4, 211.31, 260.97, 201.24, 257.95, 184.63, 266.51, 174.06, 277.08, 175.06, 282.62, 178.08, 284.63, 187.65, 296.21, 194.19, 299.73, 203.25, 311.31, 211.31, 314.33, 227.92, 314.33, 241.51, 309.8, 247.55, 304.76, 261.64, 275.57, 265.17, 251.91, 265.17]], 'num_keypoints': 9, 'area': 4889.02015, 'iscrowd': 0, 'keypoints': [0, 0, 0, 0, 0, 0, 0, 0, 0, 263, 190, 2, 281, 189, 2, 262, 209, 2, 297, 207, 2, 248, 233, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 275, 260, 2, 300, 260, 2, 245, 248, 2, 0, 0, 0, 246, 281, 1, 0, 0, 0], 'image_id': 574497, 'bbox': [238.82, 174.06, 75.51, 91.11], 'category_id': 1, 'id': 1724355}]}
Traceback (most recent call last):
File "/content/drive/My Drive/Keypoints-of-humanpose-with-Mask-R-CNN-master/model.py", line 2194, in data_generator_keypoint
load_image_gt_keypoints(dataset, config, image_id, augment, use_mini_mask=config.USE_MINI_MASK)
File "/content/drive/My Drive/Keypoints-of-humanpose-with-Mask-R-CNN-master/model.py", line 1732, in load_image_gt_keypoints
image = dataset.load_image(image_id)
File "/content/drive/My Drive/Keypoints-of-humanpose-with-Mask-R-CNN-master/utils.py", line 418, in load_image
image = skimage.io.imread(self.image_info[image_id]['path'])
File "/usr/local/lib/python3.6/dist-packages/skimage/io/_io.py", line 48, in imread
img = call_plugin('imread', fname, plugin=plugin, **plugin_args)
File "/usr/local/lib/python3.6/dist-packages/skimage/io/manage_plugins.py", line 210, in call_plugin
return func(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/skimage/io/_plugins/imageio_plugin.py", line 10, in imread
return np.asarray(imageio_imread(*args, **kwargs))
File "/usr/local/lib/python3.6/dist-packages/imageio/core/functions.py", line 221, in imread
reader = read(uri, format, "i", **kwargs)
File "/usr/local/lib/python3.6/dist-packages/imageio/core/functions.py", line 130, in get_reader
request = Request(uri, "r" + mode, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/imageio/core/request.py", line 125, in init
self._parse_uri(uri)
File "/usr/local/lib/python3.6/dist-packages/imageio/core/request.py", line 273, in _parse_uri
raise FileNotFoundError("No such file: '%s'" % fn)
FileNotFoundError: No such file: '/content/drive/My Drive/cocodataset/train2017/000000574497.jpg'
ERROR:root:Error processing image {'id': 574497, 'source': 'coco', 'path': '/content/drive/My Drive/cocodataset//train2017/000000574497.jpg', 'width': 640, 'height': 418, 'annotations': [{'segmentation': [[238.82, 264.66, 239.33, 242.01, 243.35, 240.5, 242.85, 226.41, 250.4, 211.31, 260.97, 201.24, 257.95, 184.63, 266.51, 174.06, 277.08, 175.06, 282.62, 178.08, 284.63, 187.65, 296.21, 194.19, 299.73, 203.25, 311.31, 211.31, 314.33, 227.92, 314.33, 241.51, 309.8, 247.55, 304.76, 261.64, 275.57, 265.17, 251.91, 265.17]], 'num_keypoints': 9, 'area': 4889.02015, 'iscrowd': 0, 'keypoints': [0, 0, 0, 0, 0, 0, 0, 0, 0, 263, 190, 2, 281, 189, 2, 262, 209, 2, 297, 207, 2, 248, 233, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 275, 260, 2, 300, 260, 2, 245, 248, 2, 0, 0, 0, 246, 281, 1, 0, 0, 0], 'image_id': 574497, 'bbox': [238.82, 174.06, 75.51, 91.11], 'category_id': 1, 'id': 1724355}]}
Traceback (most recent call last):
File "/content/drive/My Drive/Keypoints-of-humanpose-with-Mask-R-CNN-master/model.py", line 2194, in data_generator_keypoint
load_image_gt_keypoints(dataset, config, image_id, augment, use_mini_mask=config.USE_MINI_MASK)
File "/content/drive/My Drive/Keypoints-of-humanpose-with-Mask-R-CNN-master/model.py", line 1732, in load_image_gt_keypoints
image = dataset.load_image(image_id)
File "/content/drive/My Drive/Keypoints-of-humanpose-with-Mask-R-CNN-master/utils.py", line 418, in load_image
image = skimage.io.imread(self.image_info[image_id]['path'])
File "/usr/local/lib/python3.6/dist-packages/skimage/io/_io.py", line 48, in imread
img = call_plugin('imread', fname, plugin=plugin, **plugin_args)
File "/usr/local/lib/python3.6/dist-packages/skimage/io/manage_plugins.py", line 210, in call_plugin
return func(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/skimage/io/_plugins/imageio_plugin.py", line 10, in imread
return np.asarray(imageio_imread(*args, **kwargs))
File "/usr/local/lib/python3.6/dist-packages/imageio/core/functions.py", line 221, in imread
reader = read(uri, format, "i", **kwargs)
File "/usr/local/lib/python3.6/dist-packages/imageio/core/functions.py", line 130, in get_reader
request = Request(uri, "r" + mode, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/imageio/core/request.py", line 125, in init
self._parse_uri(uri)
File "/usr/local/lib/python3.6/dist-packages/imageio/core/request.py", line 273, in _parse_uri
raise FileNotFoundError("No such file: '%s'" % fn)
FileNotFoundError: No such file: '/content/drive/My Drive/cocodataset/train2017/000000574497.jpg'