add Trackers Playground demo with tracking UI, class filtering, and video examples

README.md

@@ -1,14 +1,12 @@
 ---
-title: Trackers
-emoji: 🏃
-colorFrom: yellow
-colorTo: yellow
+title: Roboflow Trackers
+emoji: 🔥
+colorFrom: purple
+colorTo: green
 sdk: gradio
-sdk_version: 6.5.1
+sdk_version: 6.3.0
 app_file: app.py
-pinned: false
+suggested_hardware: l4x1
 license: apache-2.0
-short_description: Detect objects with RF-DETR and track them with Trackers.
+python_version: '3.11'
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,420 @@
+"""Gradio app for the trackers library — run object tracking on uploaded videos."""
+
+from __future__ import annotations
+
+import subprocess
+import tempfile
+from pathlib import Path
+
+import cv2
+import gradio as gr
+
+MAX_DURATION_SECONDS = 30
+
+MODELS = [
+    "rfdetr-nano",
+    "rfdetr-small",
+    "rfdetr-medium",
+    "rfdetr-large",
+    "rfdetr-seg-nano",
+    "rfdetr-seg-small",
+    "rfdetr-seg-medium",
+    "rfdetr-seg-large",
+]
+
+TRACKERS = ["bytetrack", "sort"]
+
+COCO_CLASSES = [
+    "person",
+    "bicycle",
+    "car",
+    "motorcycle",
+    "airplane",
+    "bus",
+    "truck",
+    "cat",
+    "dog",
+    "sports ball",
+]
+
+VIDEO_EXAMPLES = [
+    [
+        "https://storage.googleapis.com/com-roboflow-marketing/supervision/video-examples/bikes-1280x720-1.mp4",
+        "rfdetr-small",
+        "bytetrack",
+        0.2,
+        30,
+        0.3,
+        3,
+        0.1,
+        0.6,
+        [],
+        True,
+        True,
+        False,
+        False,
+        True,
+        False,
+    ],
+    [
+        "https://storage.googleapis.com/com-roboflow-marketing/supervision/video-examples/bikes-1280x720-2.mp4",
+        "rfdetr-seg-small",
+        "sort",
+        0.2,
+        30,
+        0.3,
+        3,
+        0.3,
+        0.6,
+        [],
+        True,
+        True,
+        False,
+        False,
+        True,
+        True,
+    ],
+    [
+        "https://storage.googleapis.com/com-roboflow-marketing/supervision/video-examples/cars-1280x720-1.mp4",
+        "rfdetr-small",
+        "bytetrack",
+        0.2,
+        30,
+        0.3,
+        3,
+        0.1,
+        0.6,
+        ["car"],
+        True,
+        True,
+        False,
+        True,
+        False,
+        False,
+    ],
+    [
+        "https://storage.googleapis.com/com-roboflow-marketing/supervision/video-examples/jets-1280x720-1.mp4",
+        "rfdetr-small",
+        "bytetrack",
+        0.2,
+        30,
+        0.3,
+        3,
+        0.1,
+        0.6,
+        [],
+        True,
+        True,
+        False,
+        False,
+        False,
+        False,
+    ],
+    [
+        "https://storage.googleapis.com/com-roboflow-marketing/supervision/video-examples/jets-1280x720-2.mp4",
+        "rfdetr-seg-small",
+        "bytetrack",
+        0.2,
+        30,
+        0.3,
+        3,
+        0.1,
+        0.6,
+        [],
+        True,
+        True,
+        False,
+        False,
+        True,
+        False,
+    ],
+    [
+        "https://storage.googleapis.com/com-roboflow-marketing/supervision/video-examples/vehicles-1280x720.mp4",
+        "rfdetr-small",
+        "bytetrack",
+        0.2,
+        30,
+        0.3,
+        3,
+        0.1,
+        0.6,
+        [],
+        True,
+        True,
+        True,
+        False,
+        True,
+        False,
+    ],
+]
+
+
+def _get_video_duration(path: str) -> float:
+    """Return video duration in seconds using OpenCV."""
+    cap = cv2.VideoCapture(path)
+    if not cap.isOpened():
+        raise gr.Error("Could not open the uploaded video.")
+    fps = cap.get(cv2.CAP_PROP_FPS)
+    frame_count = cap.get(cv2.CAP_PROP_FRAME_COUNT)
+    cap.release()
+    if fps <= 0:
+        raise gr.Error("Could not determine video frame rate.")
+    return frame_count / fps
+
+
+def track(
+    video_path: str,
+    model: str,
+    tracker: str,
+    confidence: float,
+    lost_track_buffer: int,
+    track_activation_threshold: float,
+    minimum_consecutive_frames: int,
+    minimum_iou_threshold: float,
+    high_conf_det_threshold: float,
+    classes: list[str] | None = None,
+    show_boxes: bool = True,
+    show_ids: bool = True,
+    show_labels: bool = False,
+    show_confidence: bool = False,
+    show_trajectories: bool = False,
+    show_masks: bool = False,
+) -> str:
+    """Run tracking on the uploaded video and return the output path."""
+    if video_path is None:
+        raise gr.Error("Please upload a video.")
+
+    duration = _get_video_duration(video_path)
+    if duration > MAX_DURATION_SECONDS:
+        raise gr.Error(
+            f"Video is {duration:.1f}s long. "
+            f"Maximum allowed duration is {MAX_DURATION_SECONDS}s."
+        )
+
+    tmp_dir = tempfile.mkdtemp()
+    output_path = str(Path(tmp_dir) / "output.mp4")
+
+    cmd = [
+        "trackers",
+        "track",
+        "--source",
+        video_path,
+        "--output",
+        output_path,
+        "--overwrite",
+        "--model",
+        model,
+        "--tracker",
+        tracker,
+        "--model.confidence",
+        str(confidence),
+        "--tracker.lost_track_buffer",
+        str(lost_track_buffer),
+        "--tracker.track_activation_threshold",
+        str(track_activation_threshold),
+        "--tracker.minimum_consecutive_frames",
+        str(minimum_consecutive_frames),
+        "--tracker.minimum_iou_threshold",
+        str(minimum_iou_threshold),
+    ]
+
+    # ByteTrack extra param
+    if tracker == "bytetrack":
+        cmd += ["--tracker.high_conf_det_threshold", str(high_conf_det_threshold)]
+
+    if classes:
+        cmd += ["--classes", ",".join(classes)]
+
+    if show_boxes:
+        cmd += ["--show-boxes"]
+    else:
+        cmd += ["--no-boxes"]
+    if show_ids:
+        cmd += ["--show-ids"]
+    if show_labels:
+        cmd += ["--show-labels"]
+    if show_confidence:
+        cmd += ["--show-confidence"]
+    if show_trajectories:
+        cmd += ["--show-trajectories"]
+    if show_masks:
+        cmd += ["--show-masks"]
+
+    result = subprocess.run(cmd, capture_output=True, text=True)  # noqa: S603
+    if result.returncode != 0:
+        raise gr.Error(f"Tracking failed:\n{result.stderr[-500:]}")
+
+    return output_path
+
+
+with gr.Blocks(title="Trackers Playground 🔥") as demo:
+    gr.Markdown(
+        "# Trackers Playground 🔥\n\n"
+        "Upload a video, detect COCO objects with "
+        "[RF-DETR](https://github.com/roboflow-ai/rf-detr) and track them with "
+        "[Trackers](https://github.com/roboflow/trackers)."
+    )
+
+    with gr.Row():
+        input_video = gr.Video(label="Input Video")
+        output_video = gr.Video(label="Tracked Video")
+
+    track_btn = gr.Button(value="Track", variant="primary")
+
+    with gr.Row():
+        model_dropdown = gr.Dropdown(
+            choices=MODELS,
+            value="rfdetr-small",
+            label="Detection Model",
+        )
+        tracker_dropdown = gr.Dropdown(
+            choices=TRACKERS,
+            value="bytetrack",
+            label="Tracker",
+        )
+
+    with gr.Accordion("Configuration", open=False):
+        with gr.Row():
+            with gr.Column():
+                gr.Markdown("### Model")
+                confidence_slider = gr.Slider(
+                    minimum=0.0,
+                    maximum=1.0,
+                    value=0.2,
+                    step=0.05,
+                    label="Detection Confidence",
+                    info="Minimum score for a detection to be kept.",
+                )
+                class_filter = gr.CheckboxGroup(
+                    choices=COCO_CLASSES,
+                    value=[],
+                    label="Filter Classes",
+                    info="Only track selected classes. None selected means all.",
+                )
+
+            with gr.Column():
+                gr.Markdown("### Tracker")
+                lost_track_buffer_slider = gr.Slider(
+                    minimum=1,
+                    maximum=120,
+                    value=30,
+                    step=1,
+                    label="Lost Track Buffer",
+                    info="Frames to keep a lost track before removing it.",
+                )
+                track_activation_slider = gr.Slider(
+                    minimum=0.0,
+                    maximum=1.0,
+                    value=0.3,
+                    step=0.05,
+                    label="Track Activation Threshold",
+                    info="Minimum score for a track to be activated.",
+                )
+                min_consecutive_slider = gr.Slider(
+                    minimum=1,
+                    maximum=10,
+                    value=2,
+                    step=1,
+                    label="Minimum Consecutive Frames",
+                    info="Detections needed before a track is confirmed.",
+                )
+                min_iou_slider = gr.Slider(
+                    minimum=0.0,
+                    maximum=1.0,
+                    value=0.1,
+                    step=0.05,
+                    label="Minimum IoU Threshold",
+                    info="Overlap required to match a detection to a track.",
+                )
+                high_conf_slider = gr.Slider(
+                    minimum=0.0,
+                    maximum=1.0,
+                    value=0.6,
+                    step=0.05,
+                    label="High Confidence Detection Threshold",
+                    info="Detections above this are matched first (ByteTrack only).",
+                )
+
+            with gr.Column():
+                gr.Markdown("### Visualization")
+                show_boxes_checkbox = gr.Checkbox(
+                    value=True,
+                    label="Show Boxes",
+                    info="Draw bounding boxes around detections.",
+                )
+                show_ids_checkbox = gr.Checkbox(
+                    value=True,
+                    label="Show IDs",
+                    info="Display track ID for each object.",
+                )
+                show_labels_checkbox = gr.Checkbox(
+                    value=False,
+                    label="Show Labels",
+                    info="Display class name for each detection.",
+                )
+                show_confidence_checkbox = gr.Checkbox(
+                    value=False,
+                    label="Show Confidence",
+                    info="Display detection confidence score.",
+                )
+                show_trajectories_checkbox = gr.Checkbox(
+                    value=False,
+                    label="Show Trajectories",
+                    info="Draw motion path for each tracked object.",
+                )
+                show_masks_checkbox = gr.Checkbox(
+                    value=False,
+                    label="Show Masks",
+                    info="Draw segmentation masks (seg models only).",
+                )
+
+    gr.Examples(
+        examples=VIDEO_EXAMPLES,
+        fn=track,
+        cache_examples=True,
+        inputs=[
+            input_video,
+            model_dropdown,
+            tracker_dropdown,
+            confidence_slider,
+            lost_track_buffer_slider,
+            track_activation_slider,
+            min_consecutive_slider,
+            min_iou_slider,
+            high_conf_slider,
+            class_filter,
+            show_boxes_checkbox,
+            show_ids_checkbox,
+            show_labels_checkbox,
+            show_confidence_checkbox,
+            show_trajectories_checkbox,
+            show_masks_checkbox,
+        ],
+        outputs=output_video,
+    )
+
+    track_btn.click(
+        fn=track,
+        inputs=[
+            input_video,
+            model_dropdown,
+            tracker_dropdown,
+            confidence_slider,
+            lost_track_buffer_slider,
+            track_activation_slider,
+            min_consecutive_slider,
+            min_iou_slider,
+            high_conf_slider,
+            class_filter,
+            show_boxes_checkbox,
+            show_ids_checkbox,
+            show_labels_checkbox,
+            show_confidence_checkbox,
+            show_trajectories_checkbox,
+            show_masks_checkbox,
+        ],
+        outputs=output_video,
+    )
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,2 @@
+gradio>=6.3.0,<6.4.0
+trackers[detection]@git+https://github.com/roboflow/trackers.git