rewe

app.py

@@ -1,26 +1,28 @@
-
 import cv2
-from ultralytics import YOLO
 import numpy as np
 import torch
-import threading
-from queue import Queue, Empty
-import time
 import gradio as gr
 from gradio_webrtc import WebRTC
-from huggingface_hub import hf_hub_download
-from inference import YOLOv10
-
-model_file = hf_hub_download(
-    repo_id="onnx-community/yolov10n", filename="onnx/model.onnx"
-)
+from ultralytics import YOLO
 
-model = YOLOv10(model_file)
+# Load the YOLOv5s-nano model (Make sure it's available or downloaded via CLI or path)
+model = YOLO("yolov5sn.pt")  # You can also use a local path
 
 def detection(image, conf_threshold=0.3):
-    image = cv2.resize(image, (model.input_width, model.input_height))
-    new_image = model.detect_objects(image, conf_threshold)
-    return new_image
+    # Convert RGB to BGR (OpenCV uses BGR)
+    image_bgr = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+
+    # Inference with confidence threshold
+    results = model(image_bgr, conf=conf_threshold)
+
+    # Draw results on image
+    annotated = results[0].plot()  # This returns a numpy array with drawings
+
+    # Convert back to RGB for display
+    return cv2.cvtColor(annotated, cv2.COLOR_BGR2RGB)
+
+# Optional: Add your custom RTC config if needed
+rtc_configuration = {}
 
 css = """.my-group {max-width: 600px !important; max-height: 600px !important;}
          .my-column {display: flex !important; justify-content: center !important; align-items: center !important;}"""
@@ -29,7 +31,7 @@ with gr.Blocks(css=css) as demo:
     gr.HTML(
         """
         <h1 style='text-align: center'>
-        YOLOv10 Webcam Stream (Powered by WebRTC ⚡️)
+        YOLOv5sn Webcam Stream (Powered by WebRTC ⚡️)
         </h1>
         """
     )
@@ -55,4 +57,4 @@ if __name__ == "__main__":
         server_port=7860,
         show_error=True,
         debug=True
-    )
+    )