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app.py

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+from ultralytics import YOLO
+import cv2
+import numpy as np
+import gradio as gr
+import torch
+
+# Load YOLOv5n6 model
+model = YOLO('yolov5n6.pt')
+
+# Set the confidence threshold and IOU
+model.conf = 0.25  # confidence threshold
+model.iou = 0.45  # IOU threshold
+model.agnostic = False
+model.multi_label = False
+model.max_det = 100  # max number of detections
+
+# Low-resolution for inference
+LOW_RES = (320, 180)
+
+def detect_and_draw(frame):
+    # Create low-res copy
+    low_res_frame = cv2.resize(frame, LOW_RES)
+    
+    # Perform detection
+    results = model(low_res_frame, verbose=False)
+
+    # Scale bounding boxes
+    scale_x = frame.shape[1] / LOW_RES[0]
+    scale_y = frame.shape[0] / LOW_RES[1]
+
+    # Draw bounding boxes on high-res frame
+    for detection in results[0].boxes.data:
+        x1, y1, x2, y2, conf, cls = detection
+        x1, y1, x2, y2 = int(x1*scale_x), int(y1*scale_y), int(x2*scale_x), int(y2*scale_y)
+        label = f"{results[0].names[int(cls)]} {conf:.2f}"
+        cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
+        cv2.putText(frame, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
+
+    return frame
+
+# Define your stream URL
+stream_url = "https://edge01.london.nginx.hdontap.com/hosb5/ng_showcase-coke_bottle-street_fixed.stream/chunklist_w464099566.m3u8"
+
+def process_stream():
+    cap = cv2.VideoCapture(stream_url)
+    frame_count = 0
+    while cap.isOpened():
+        ret, frame = cap.read()
+        if not ret:
+            break
+
+        frame_count += 3
+        if frame_count % 30 == 0:
+            result = detect_and_draw(frame)
+            result_rgb = cv2.cvtColor(result, cv2.COLOR_BGR2RGB)
+            yield result_rgb
+
+    cap.release()
+
+iface = gr.Interface(
+    fn=process_stream,
+    inputs=None,
+    outputs="image",
+    live=True,
+    title="Fast Real-time Object Detection with High-Res Output",
+    description="Live stream processed with YOLOv5n6 on low-res frames, results drawn on high-res frames."
+)
+
+if __name__ == "__main__":
+    if torch.cuda.is_available():
+        model.to('cuda')
+    #iface.queue()
+    iface.launch()

requirements.txt

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+ultralytics
+opencv-python
+gradio
+torch

yolov5n6.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:496c05a2b991da15acc6c4408c63da287f2513a46c6756618776d4dd71170781
+size 7190229