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README.md

@@ -1,12 +1,13 @@
 ---
-title: ObjectTrackingYOLOv8
-emoji: 📉
-colorFrom: purple
+title: ObjectTrackingWithYOLOv8
+emoji: 🏢
+colorFrom: red
 colorTo: blue
 sdk: gradio
-sdk_version: 3.45.1
+sdk_version: 3.42.0
 app_file: app.py
 pinned: false
+license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,39 @@
+import gradio as gr
+import supervision as sv
+from ultralytics import YOLO
+import numpy as np
+import cv2  # for video to image conversion
+
+
+model = YOLO('yolov8s.pt')
+byte_tracker = sv.ByteTrack()
+annotator = sv.BoxAnnotator()
+
+
+def process_video(frame):
+    results = model(frame)[0]
+    detections = sv.Detections.from_ultralytics(results)
+    detections = byte_tracker.update_with_detections(detections)
+    labels = [
+         f"#{tracker_id} {model.model.names[class_id]} {confidence:0.2f}"
+         for _, _, confidence, class_id, tracker_id
+         in detections
+    ]
+    yield  annotator.annotate(scene=frame.copy(),
+                               detections=detections, labels=labels)
+
+
+title = "Object Tracking (w/ YOLOv8)"
+with gr.Blocks() as io:
+    gr.Markdown(f"<center><h1>{title}</h1></center>")
+    with gr.Row():
+        with gr.Column():
+            input_image = gr.Image(source='webcam', streaming=True)
+            input_button = gr.Button()
+        with gr.Column():
+            output_image = gr.Image()
+        input_image.change(process_video, inputs=[input_image], outputs=[output_image], show_progress=False)
+        
+io.queue()
+
+io.launch()

requirements.txt

@@ -0,0 +1,2 @@
+ultralytics
+supervision