Upload LLaVA-Next-3D/data_precessing/sam2_tracking.py with huggingface_hub

LLaVA-Next-3D/data_precessing/sam2_tracking.py

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+import glob
+import copy
+import json
+import pdb
+from tqdm import tqdm
+
+dirs = glob.glob('extra_data/SA-V/sav_train/sav_*')
+
+paths = []
+for dir_ in dirs:
+    paths += glob.glob(dir_ + '/*_object_*.json')
+
+llava_data = []
+
+for sample_id, path in enumerate(tqdm(paths)):
+    data = json.load(open(path, 'r'))
+    item = {"id": 0, 
+            "video": "",
+            "conversations": [{"value": "<image> Identify the object according to the following bounding box: \n <OBJ>", "from": "human"}, \
+                                {"value": "<OBJ>", "from": "gpt"}], 
+            "metadata": {"dataset": "sam2_tracking", "box_info": ""}}
+    item["id"] = sample_id
+    item["video"] = path[0:44] + '.mp4'
+    item["metadata"]["box_info"] = data
+
+    llava_data.append(item)
+
+json.dump(llava_data, open('extra_data/annotation/sam2_tracking_llava_format.json', 'w'), indent=4)