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app.py

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+from torchyolo import YoloHub
+import gradio as gr
+
+""" 
+Paper Implementation
+#"kadirnar/OcSort"
+#"kadirnar/SORT"
+"""
+
+def object_tracker(
+    source: str,
+    model_type: str,
+    model_path: str,
+    tracker_type: str,
+    tracker_config_path: str,
+):
+    model = YoloHub(
+        config_path="default_config.yaml",
+        model_type=model_type,
+        model_path=model_path,
+    )
+
+    model.predict(
+        source=source,
+        tracker_type=tracker_type,
+        tracker_config_path=tracker_config_path,
+    )
+    return 'output.mp4'
+       
+
+inputs = [
+    gr.Video(),
+    gr.inputs.Dropdown(
+        label="Model Type",
+        choices=["yolov5", "yolov6", "yolov8"],
+        default="yolov5",
+    ),
+    gr.inputs.Dropdown(
+        label="Model Path",
+        choices=[
+            "kadirnar/yolov5s6-v6.0",
+            "kadirnar/yolov6m-v3.0",
+            "kadirnar/yolov8n-v8.0",
+        ],
+        default="kadirnar/yolov5s6-v6.",
+    ),
+    gr.inputs.Dropdown(
+        label="Tracker Type",
+        choices=["NORFAIR", "STRONGSORT", "OCSORT", "BYTETRACK", "SORT"],
+        default="NORFAIR",
+    ),
+    gr.inputs.Dropdown(
+        label="Tracker Config Path",
+        choices=[
+            "tracker/norfair_track.yaml",
+            "tracker/strong_sort.yaml",
+            "tracker/oc_sort.yaml",
+            "tracker/byte_track.yaml",
+            "tracker/sort_track.yaml",
+        ],
+        default="tracker/norfair_track.yaml",
+    ),
+]
+examples = [
+    [
+        "test.mp4",
+        "yolov5",
+        "kadirnar/yolov5s6-v6.0",
+        "NORFAIR",
+        "tracker/norfair_track.yaml"
+    ],
+]
+outputs = gr.Video()
+title = "TorchYolo: YOLO Series Object Detection and Track Algorithm Library"
+
+demo_app = gr.Interface(
+    fn=object_tracker,
+    inputs=inputs,
+    examples=examples,
+    outputs=outputs,
+    title=title,
+    cache_examples=False,
+    theme='huggingface',
+)
+demo_app.launch(debug=True, enable_queue=True)

default_config.yaml

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+DETECTOR_CONFIG:
+  # The threshold for the IOU score
+  IOU_TH: 0.45
+  # The threshold for the confidence score
+  CONF_TH: 0.25
+  # The size of the image
+  IMAGE_SIZE: 640
+  # The device to run the detector
+  DEVICE: cuda:0
+  # F16 precision
+  HALF: False
+  # The path of the yolov6 label file
+  YOLOV6_YAML_FILE: torchyolo/configs/yolov6/coco.yaml
+  # The path of the yolovx config file
+  YOLOX_CONFIG_PATH: configs.yolox.yolox_s
+  # The path of the Hugging Face model
+  HUGGING_FACE_MODEL: True 
+
+DATA_CONFIG:
+  # The path of the output video
+  OUTPUT_PATH: output.mp4
+  # Save the video
+  SHOW: False 
+  # Show the video
+  SAVE: True

packages.txt

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+ffmpeg

requirements.txt

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+ultralytics
+yolov5
+yolov6detect 
+torchyolo
+norfair-tracker
+ocsort
+sort-track

tracker/byte_track.yaml

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+BYTE_TRACK:
+  # The name of the sort
+  TRACK_BUFFER: 25
+  # The buffer for the track
+  FRAME_RATE: 30
+  # The frame rate of the video
+  

tracker/norfair_track.yaml

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+NORFAIR_TRACK:
+  DISTANCE_FUNCTION: "frobenius" # mean_manhattan, mean_euclidean, iou, iou_opt
+  DISTANCE_THRESHOLD: 500
+  HIT_COUNTER_MAX: 15
+  INITIALIZATION_DELAY: null
+  POINTWISE_HIT_COUNTER_MAX: 4
+  DETECTION_THRESHOLD: 0
+  PAST_DETECTIONS_LENGTH: 4
+  REID_DISTANCE_THRESHOLD: 0
+  REID_HIT_COUNTER_MAX: null

tracker/oc_sort.yaml

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+OC_SORT:
+  # The name of the sort
+  CONF_THRESHOLD: 0.05 
+  # The threshold for the confidence score
+  IOU_THRESHOLD: 0.3
+  # The threshold for the IOU score
+  MAX_AGE: 30
+  # The maximum age of the track
+  MIN_HITS: 3
+  # The minimum number of hits for the track
+  DELTA_T: 3
+  # The time interval between two frames
+  ASSO_FUNC: "iou"  # giou, ciou, diou, ct_dist
+  # The association function
+  INERTIA: 0.2
+  # The inertia of the track
+  USE_BYTE: False
+  # Whether to use byte as the unit of the bounding box

tracker/sort_track.yaml

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+SORT_TRACK:
+  # The name of the sort
+  MAX_AGE: 1
+  # The maximum number of frames to keep alive a track without associated detections
+  MIN_HITS: 3
+  # The minimum number of associated detections before track initialization

tracker/strong_sort.yaml

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+STRONG_SORT:
+  ECC: True              # activate camera motion compensation
+  MC_LAMBDA: 0.995       # matching with both appearance (1 - MC_LAMBDA) and motion cost
+  EMA_ALPHA: 0.9         # updates  appearance  state in  an exponential moving average manner
+  MAX_DIST: 0.2          # The matching threshold. Samples with larger distance are considered an invalid match
+  MAX_IOU_DISTANCE: 0.7  # Gating threshold. Associations with cost larger than this value are disregarded.
+  MAX_AGE: 30            # Maximum number of missed misses before a track is deleted
+  N_INIT: 3              # Number of frames that a track remains in initialization phase
+  NN_BUDGET: 100         # Maximum size of the appearance descriptors gallery