@@ -0,0 +1,98 @@
+import os
+import cv2
+import multiprocessing as mp
+import numpy as np
+import time
+import psutil
+import tflite_runtime.interpreter as tflite  
+
+ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+MODEL_PATH = os.path.join(ROOT, "model_int8.tflite")
+
+def camera_worker(frame_queue):
+    cap = cv2.VideoCapture(0)
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            continue
+        if not frame_queue.full():
+            frame_queue.put(frame)
+
+def classifier_worker(frame_queue, result_queue):
+    interpreter = tflite.Interpreter(model_path=MODEL_PATH, num_threads=2)
+    interpreter.allocate_tensors()
+
+    input_details = interpreter.get_input_details()
+    output_details = interpreter.get_output_details()
+    
+    input_shape = input_details[0]['shape']
+    height, width = input_shape[1], input_shape[2]
+
+    while True:
+        if not frame_queue.empty():
+            frame = frame_queue.get()
+            
+            resized_frame = cv2.resize(frame, (width, height))
+            
+            input_data = np.expand_dims(resized_frame, axis=0)
+
+            if input_details[0]['dtype'] == np.float32:
+                input_data = input_data.astype(np.float32) / 255.0
+            else:
+                input_data = input_data.astype(input_details[0]['dtype'])
+
+            interpreter.set_tensor(input_details[0]['index'], input_data)
+            interpreter.invoke()
+
+            output_data = interpreter.get_tensor(output_details[0]['index'])
+            
+            pred_idx = np.argmax(output_data)
+            pred_text = f"Class: {pred_idx}" 
+
+            result_queue.put((frame, pred_text))
+
+def display_worker(result_queue):
+    prev_frame_time = 0
+    psutil.cpu_percent()
+    
+    while True:
+        if not result_queue.empty():
+            frame, pred = result_queue.get()
+            
+            new_frame_time = time.time()
+            if prev_frame_time != 0:
+                fps = 1 / (new_frame_time - prev_frame_time)
+            else:
+                fps = 0
+            prev_frame_time = new_frame_time
+            
+            cpu_usage = psutil.cpu_percent()
+            
+            fps_text = f"FPS: {int(fps)}"
+            cpu_text = f"CPU: {cpu_usage}%"
+
+            cv2.putText(frame, str(pred), (30,30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,255,0), 2)
+            cv2.putText(frame, fps_text, (30,70), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,0,0), 2)
+            cv2.putText(frame, cpu_text, (30,110), cv2.FONT_HERSHEY_SIMPLEX, 1, (0,0,255), 2)
+
+            cv2.imshow("Multiprocess Classifier", frame)
+
+        if cv2.waitKey(1) == 27:
+            break
+
+if __name__=="__main__":
+    frame_queue = mp.Queue(maxsize=5)
+    result_queue = mp.Queue(maxsize=5)
+
+    p1 = mp.Process(target=camera_worker, args=(frame_queue,))
+    p2 = mp.Process(target=classifier_worker, args=(frame_queue, result_queue))
+    p3 = mp.Process(target=display_worker, args=(result_queue,))
+
+    p1.start()
+    p2.start()
+    p3.start()
+
+    p1.join()
+    p2.join()
+    p3.join()
+