Update app.py

app.py

@@ -1,48 +1,23 @@
-# Flask Backend (app.py)
-from flask import Flask, render_template, Response, jsonify
+from flask import Flask, render_template, jsonify, request, send_file
 import psutil
+import json
+from ultralytics import YOLO
 import cv2
 import numpy as np
-from ultralytics import YOLO
-import threading
-import queue
+from PIL import Image
+import io
+import base64
 
 app = Flask(__name__)
 modelName = "yolov9c-seg.pt"
 model = YOLO(modelName)
 
-# Global variables for frame handling
-frame_queue = queue.Queue(maxsize=2)
-processed_frame_queue = queue.Queue(maxsize=2)
-current_frame = None
-processing_active = False
-
-def process_frames():
-    global processing_active
-    while processing_active:
-        if not frame_queue.empty():
-            frame = frame_queue.get()
-            results = model(
-                frame,
-                show=False,
-                save=False,
-                show_boxes=True,
-                show_labels=True,
-                imgsz=640,
-                iou=0.1,
-                max_det=20,
-            )
-            processed_frame = results[0].plot()
-            processed_frame = cv2.cvtColor(np.array(processed_frame), cv2.COLOR_RGB2BGR)
-            
-            if processed_frame_queue.full():
-                processed_frame_queue.get()  # Remove old frame
-            processed_frame_queue.put(processed_frame)
 
 @app.route("/")
 def home():
     return render_template("index.html")
 
+
 @app.route("/sysInfo")
 def sysInfo():
     ram = psutil.virtual_memory()
@@ -51,46 +26,34 @@ def sysInfo():
     data = {"ram": ram_usage, "cpu": cpu_usage}
     return jsonify(data)
 
-def generate_frames():
-    global processing_active
-    while True:
-        if not processed_frame_queue.empty():
-            frame = processed_frame_queue.get()
-            ret, buffer = cv2.imencode('.jpg', frame)
-            frame = buffer.tobytes()
-            yield (b'--frame\r\n'
-                   b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')
-
-@app.route('/video_feed')
-def video_feed():
-    return Response(generate_frames(),
-                    mimetype='multipart/x-mixed-replace; boundary=frame')
-
-@app.route('/start_processing')
-def start_processing():
-    global processing_active
-    if not processing_active:
-        processing_active = True
-        threading.Thread(target=process_frames, daemon=True).start()
-    return jsonify({"status": "started"})
-
-@app.route('/stop_processing')
-def stop_processing():
-    global processing_active
-    processing_active = False
-    return jsonify({"status": "stopped"})
-
-@app.route('/update_frame', methods=['POST'])
-def update_frame():
-    global current_frame
-    data = request.get_json()
-    frame_data = np.array(data['frame'])
-    
-    if frame_queue.full():
-        frame_queue.get()  # Remove old frame
-    frame_queue.put(frame_data)
-    
-    return jsonify({"status": "success"})
 
-if __name__ == "__main__":
-    app.run(debug=True, host="0.0.0.0", port=7860)
+@app.route("/processor", methods=["POST"])
+def processor():
+    global modelName, model
+    image = request.form.get("image")
+    modelNameForm = request.form.get("model", modelName)
+    if modelNameForm != modelName:
+        modelName = modelNameForm
+        model = YOLO(modelName)
+    image = image.split(",")[1]
+    image = base64.b64decode(image)
+    image = Image.open(io.BytesIO(image))
+    image = np.array(image)
+    results = model(
+        image,
+        show=False,
+        save=False,
+        show_boxes=True,
+        show_labels=True,
+        imgsz=640,
+        iou=0.1,
+        max_det=20,
+    )
+    image = results[0].plot()
+    image = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+    image = cv2.imencode(".jpg", image)[1].tobytes()
+    image = base64.b64encode(image).decode("utf-8")
+    return jsonify({"image": image})
+
+
+app.run(debug=True, host="0.0.0.0", port=7860)