FileNotFoundError: CocoDataset: [Errno 2] No such file or directory: 'data/coco/annotations/instances_train2017.json'

[bipin-saha]

Error Message

Traceback (most recent call last):
  File "/usr/local/lib/python3.7/dist-packages/mmcv/utils/registry.py", line 69, in build_from_cfg
    return obj_cls(**args)
  File "/content/mmdetection/mmdet/datasets/custom.py", line 95, in __init__
    self.data_infos = self.load_annotations(local_path)
  File "/content/mmdetection/mmdet/datasets/coco.py", line 72, in load_annotations
    self.coco = COCO(ann_file)
  File "/content/mmdetection/mmdet/datasets/api_wrappers/coco_api.py", line 23, in __init__
    super().__init__(annotation_file=annotation_file)
  File "/usr/local/lib/python3.7/dist-packages/pycocotools/coco.py", line 81, in __init__
    with open(annotation_file, 'r') as f:
FileNotFoundError: [Errno 2] No such file or directory: 'data/coco/annotations/instances_train2017.json'

I am trying to train a model using TridentNet, and the dataset is COCO.

I have passed my image locations and annotation via cfg

# The new config inherits a base config to highlight the necessary modification
_base_ = '/content/mmdetection/configs/tridentnet/tridentnet_r50_caffe_1x_coco.py'

# We also need to change the num_classes in head to match the dataset's annotation
model = dict(
    roi_head=dict(
        bbox_head=dict(num_classes=16),
        mask_head=dict(num_classes=16)))

# Modify dataset related settings
dataset_type = 'COCODataset'
classes = ('A', 'B','C', 'D','E', 'F','G', 'H','I', 'J','K', 'L','M', 'N','O', 'P',)

import os
MODELS_CONFIG = {
    'tridentnet_r50_caffe_1x_coco.py': {
        'config_file': '/content/mmdetection/configs/tridentnet/tridentnet_r50_caffe_1x_coco.py'
    }
}

# Pick the model you want to use
selected_model = 'tridentnet_r50_caffe_1x_coco.py' # chose any config you want from the MODELS_CONFIG

# Name of the config file.
config_file = MODELS_CONFIG[selected_model]['config_file']

config_fname = os.path.join('mmdetection', config_file)
assert os.path.isfile(config_fname), '`{}` not exist'.format(config_fname)
config_fname

from mmcv import Config
cfg = Config.fromfile('/content/mmdetection/configs/tridentnet/tridentnet_r50_caffe_1x_coco.py')

cfg.data.train.ann_file = '/content/mmdetection/RoadVehicle-3/train/_annotations.coco.json'
cfg.data.train.img_prefix = '/content/mmdetection/RoadVehicle-3/train'

cfg.data.val.ann_file = '/content/mmdetection/RoadVehicle-3/valid/_annotations.coco.json'
cfg.data.val.img_prefix = '/content/mmdetection/RoadVehicle-3/valid'

cfg.data.test.ann_file = '/content/mmdetection/RoadVehicle-3/test/_annotations.coco.json'
cfg.data.test.img_prefix = '/content/mmdetection/RoadVehicle-3/test'

And the cfg output is

{'samples_per_gpu': 2,
 'workers_per_gpu': 2,
 'train': {'type': 'CocoDataset',
  'ann_file': '/content/mmdetection/RoadVehicle-3/train/_annotations.coco.json',
  'img_prefix': '/content/mmdetection/RoadVehicle-3/train',
  'pipeline': [{'type': 'LoadImageFromFile'},
   {'type': 'LoadAnnotations', 'with_bbox': True},
   {'type': 'Resize', 'img_scale': (1333, 800), 'keep_ratio': True},
   {'type': 'RandomFlip', 'flip_ratio': 0.5},
   {'type': 'Normalize',
    'mean': [103.53, 116.28, 123.675],
    'std': [1.0, 1.0, 1.0],
    'to_rgb': False},
   {'type': 'Pad', 'size_divisor': 32},
   {'type': 'DefaultFormatBundle'},
   {'type': 'Collect', 'keys': ['img', 'gt_bboxes', 'gt_labels']}]},
 'val': {'type': 'CocoDataset',
  'ann_file': '/content/mmdetection/RoadVehicle-3/valid/_annotations.coco.json',
  'img_prefix': '/content/mmdetection/RoadVehicle-3/valid',
  'pipeline': [{'type': 'LoadImageFromFile'},
   {'type': 'MultiScaleFlipAug',
    'img_scale': (1333, 800),
    'flip': False,
    'transforms': [{'type': 'Resize', 'keep_ratio': True},
     {'type': 'RandomFlip'},
     {'type': 'Normalize',
      'mean': [103.53, 116.28, 123.675],
      'std': [1.0, 1.0, 1.0],
      'to_rgb': False},
     {'type': 'Pad', 'size_divisor': 32},
     {'type': 'ImageToTensor', 'keys': ['img']},
     {'type': 'Collect', 'keys': ['img']}]}]},
 'test': {'type': 'CocoDataset',
  'ann_file': '/content/mmdetection/RoadVehicle-3/test/_annotations.coco.json',
  'img_prefix': '/content/mmdetection/RoadVehicle-3/test',
  'pipeline': [{'type': 'LoadImageFromFile'},
   {'type': 'MultiScaleFlipAug',
    'img_scale': (1333, 800),
    'flip': False,
    'transforms': [{'type': 'Resize', 'keep_ratio': True},
     {'type': 'RandomFlip'},
     {'type': 'Normalize',
      'mean': [103.53, 116.28, 123.675],
      'std': [1.0, 1.0, 1.0],
      'to_rgb': False},
     {'type': 'Pad', 'size_divisor': 32},
     {'type': 'ImageToTensor', 'keys': ['img']},
     {'type': 'Collect', 'keys': ['img']}]}]}}

After that while running the Train.py as

!python /content/mmdetection/tools/train.py /content/mmdetection/configs/tridentnet/tridentnet_r50_caffe_1x_coco.py

Finally, I got the error as
Error Message

FileNotFoundError: [Errno 2] No such file or directory: 'data/coco/annotations/instances_train2017.json'