KuAvLab commited on
Commit
e7de586
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1 Parent(s): 38c0ca4

Update EMT.py

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Files changed (1) hide show
  1. EMT.py +17 -11
EMT.py CHANGED
@@ -266,23 +266,28 @@ class EMT(datasets.GeneratorBasedBuilder):
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  "annotation_path": annotations["test"],
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  },
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  ),
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- ]
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-
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  def _generate_examples(self, images, annotation_path):
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  """Generate dataset examples by matching images to their corresponding annotations."""
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-
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  annotations = {}
 
 
 
 
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- # Extract annotation tar file and read its contents
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- for ann_file in os.listdir(annotation_path):
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- # Ensure that we're dealing with the annotation file
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- ann_path = os.path.join(annotation_path, ann_file)
 
 
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  if os.path.isdir(ann_path):
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  continue # Skip directories
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-
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  print("Processing annotation file:", ann_path)
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-
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  with open(ann_path, "r", encoding="utf-8") as f:
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  for line in f:
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  parts = line.strip().split()
@@ -295,7 +300,7 @@ class EMT(datasets.GeneratorBasedBuilder):
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  img_name = f"{frame_id}.jpg"
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  # Store annotation in a dictionary
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- key = f"{ann_file}/{img_name}"
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  if key not in annotations:
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  annotations[key] = []
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@@ -307,7 +312,7 @@ class EMT(datasets.GeneratorBasedBuilder):
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  "class_name": class_name,
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  }
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  )
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-
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  # Yield dataset entries
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  idx = 0
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  for file_path, file_obj in images:
@@ -322,3 +327,4 @@ class EMT(datasets.GeneratorBasedBuilder):
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  }
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  idx += 1
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  "annotation_path": annotations["test"],
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  },
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  ),
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+ ]
 
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  def _generate_examples(self, images, annotation_path):
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  """Generate dataset examples by matching images to their corresponding annotations."""
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+
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  annotations = {}
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+
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+ # Ensure we access the correct annotation subdirectory
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+ annotation_split = "train" if "train" in annotation_path else "test"
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+ ann_dir = os.path.join(annotation_path, "annotations", annotation_split)
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+ print("Looking for annotations in:", ann_dir)
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+
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+ # Extract annotation files and read their contents
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+ for ann_file in os.listdir(ann_dir):
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+ video_name = os.path.splitext(ann_file)[0] # Extract video folder name from file
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+ ann_path = os.path.join(ann_dir, ann_file)
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  if os.path.isdir(ann_path):
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  continue # Skip directories
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+
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  print("Processing annotation file:", ann_path)
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+
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  with open(ann_path, "r", encoding="utf-8") as f:
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  for line in f:
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  parts = line.strip().split()
 
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  img_name = f"{frame_id}.jpg"
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  # Store annotation in a dictionary
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+ key = f"{video_name}/{img_name}"
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  if key not in annotations:
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  annotations[key] = []
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  "class_name": class_name,
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  }
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  )
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+
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  # Yield dataset entries
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  idx = 0
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  for file_path, file_obj in images:
 
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  }
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  idx += 1
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+