Duplicate from bridgeconn/sign-dictionary-isl

Co-authored-by: Kavitha Raju <Kavitha@users.noreply.huggingface.co>

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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+*.bz2 filter=lfs diff=lfs merge=lfs -text
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+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
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+*.parquet filter=lfs diff=lfs merge=lfs -text
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+*.pickle filter=lfs diff=lfs merge=lfs -text
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+*.pth filter=lfs diff=lfs merge=lfs -text
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+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
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+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
+*.flac filter=lfs diff=lfs merge=lfs -text
+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.ogg filter=lfs diff=lfs merge=lfs -text
+*.wav filter=lfs diff=lfs merge=lfs -text
+# Image files - uncompressed
+*.bmp filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.tiff filter=lfs diff=lfs merge=lfs -text
+# Image files - compressed
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+# Video files - compressed
+*.mp4 filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+configs:
+  - config_name: all
+    data_files:
+      - split: train
+        path: "*-train.tar"
+    default: true
+language: ins
+license: cc-by-sa-4.0
+datasets:
+- bridgeconn/sign-dictionary-isl
+tags:
+- video
+- parallel-corpus
+- low-resource-languages
+---
+
+
+# Dataset Card for Sign Dictionary Dataset
+
+This dataset contains Indian sign language videos with one gloss per video. There are 3077 seperate lex items or glosses included.
+The dataset is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0).
+
+
+## Dataset Details
+
+There is a total of 2.5 hours of sign videos.
+
+## Dataset Description
+
+- Segmented sign videos
+- Pose estimation data in the following formats
+  - skeletal video
+  - Frames wise body landmarks detected by dwpose as a numpy array
+  - Frames wise body landmarks detected by mediapose as .pose format
+
+## How to use
+
+```python
+import webdataset as wds
+import numpy as np
+import json
+import tempfile
+import os
+import cv2
+
+
+def main():
+	buffer_size = 1024
+	dataset = (
+	    wds.WebDataset(
+            "https://huggingface.co/datasets/bridgeconn/sign-dictionary-isl/resolve/main/shard_{00001..00002}-train.tar",
+            shardshuffle=False)
+	    .shuffle(buffer_size)
+	    .decode()
+	)
+    for sample in dataset:
+		''' Each sample contains:
+			 'mp4', 
+			 'pose-dwpose.npz', 'pose-mediapipe.pose'
+			 and 'json'
+		'''
+		# print(sample.keys())
+
+		# JSON metadata
+        json_data = sample['json']
+		print(json_data['filename']) 
+		print(json_data['transcripts'])
+        print(json_data['glosses'])
+
+		# main video
+		mp4_data = sample['mp4']
+		process_video(mp4_data)
+		
+		# dwpose results
+        dwpose_coords = sample["pose-dwpose.npz"] 
+
+		frame_poses = dwpose_coords['frames'].tolist()
+		print(f"Frames in dwpose coords: {len(frame_poses)} poses")
+		print(f"Pose coords shape: {len(frame_poses[0][0])}")
+		print(f"One point looks like [x,y]: {frame_poses[0][0][0]}")
+
+		# mediapipe results in .pose format
+		pose_format_data = sample["pose-mediapipe.pose"]
+		process_poseformat(pose_format_data)
+
+		break
+
+
+def process_poseformat(pose_format_data):
+	from pose_format import Pose
+	temp_file = None
+	try:
+		with tempfile.NamedTemporaryFile(suffix=".pose", delete=False) as tmp:
+			tmp.write(pose_format_data)
+			temp_file = tmp.name
+
+		data_buffer = open(temp_file, "rb").read()
+		pose = Pose.read(data_buffer)
+
+		print(f"Mediapipe results from pose-format: {pose.body.data.shape}")
+	except Exception as e:
+		print(f"Error processing pose-format: {e}")
+	finally:
+		if temp_file and os.path.exists(temp_file):
+			os.remove(temp_file) # Clean up the temporary file
+
+
+def process_video(mp4_data):
+	print(f"Video bytes length: {len(mp4_data)} bytes")
+
+	temp_file = None
+	try:
+		# Processing video from temporary file
+		with tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) as tmp:
+			tmp.write(mp4_data)
+			temp_file = tmp.name
+
+		cap = cv2.VideoCapture(temp_file)
+
+		if not cap.isOpened():
+			raise IOError(f"Could not open video file: {temp_file}")
+
+		# Example: Get video metadata
+		frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+		fps = cap.get(cv2.CAP_PROP_FPS)
+		width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+		height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+
+		print(f"Video Info: {frame_count} frames, {fps:.2f} FPS, {width}x{height}")
+
+		# Example: Read and display the first frame (or process as needed)
+		ret, frame = cap.read()
+		if ret:
+			print(f"First frame shape: {frame.shape}, dtype: {frame.dtype}")
+			# You can then use this frame for further processing, e.g.,
+			frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+			import matplotlib.pyplot as plt
+			plt.imshow(frame_rgb)
+			plt.title(f"Sample First Frame")
+			plt.show()
+		else:
+			print("Could not read first frame.")
+
+		cap.release()
+
+	except Exception as e:
+		print(f"Error processing external MP4: {e}")
+	finally:
+		if temp_file and os.path.exists(temp_file):
+			os.remove(temp_file) # Clean up the temporary file
+
+
+if __name__ == '__main__':
+	main()
+```
+
+
+---
+license: cc-by-sa-4.0
+---

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