Update app.py

app.py

@@ -12,11 +12,11 @@ def create_monitor_interface():
     api_key = os.getenv("GROQ_API_KEY")
     
     class SafetyMonitor:
-        def __init__(self, model_name: str = "llama-3.2-90b-vision-preview"):
+        def __init__(self, model_name: str = "mixtral-8x7b-vision"):
             self.client = Groq(api_key=api_key)
             self.model_name = model_name
-            self.max_image_size = (512, 512)  # Maximum dimensions
-            self.jpeg_quality = 50  # Reduced JPEG quality
+            self.max_image_size = (128, 128)  # Drastically reduced size
+            self.jpeg_quality = 20  # Very low quality
 
         def resize_image(self, image):
             """Resize image while maintaining aspect ratio"""
@@ -32,37 +32,33 @@ def create_monitor_interface():
                 new_height = min(self.max_image_size[1], height)
                 new_width = int(new_height * aspect)
                 
-            return cv2.resize(image, (new_width, new_height))
+            resized = cv2.resize(image, (new_width, new_height), interpolation=cv2.INTER_AREA)
+            return resized
 
         def analyze_frame(self, frame: np.ndarray) -> str:
             if frame is None:
                 return "No frame received"
                 
-            # Convert numpy array to PIL Image
+            # Convert and resize image
             if len(frame.shape) == 2:
                 frame = cv2.cvtColor(frame, cv2.COLOR_GRAY2RGB)
             elif len(frame.shape) == 3 and frame.shape[2] == 4:
                 frame = cv2.cvtColor(frame, cv2.COLOR_RGBA2RGB)
             
-            # Resize image
             frame = self.resize_image(frame)
-                
             frame_pil = PILImage.fromarray(frame)
             
-            # Convert to base64 with compression
+            # Convert to base64 with minimal size
             buffered = io.BytesIO()
-            frame_pil.save(buffered, format="JPEG", quality=self.jpeg_quality, optimize=True)
+            frame_pil.save(buffered, 
+                         format="JPEG", 
+                         quality=self.jpeg_quality, 
+                         optimize=True)
             img_base64 = base64.b64encode(buffered.getvalue()).decode('utf-8')
             
             try:
-                prompt = f"""Please analyze this image for workplace safety issues. Focus on:
-                1. PPE usage (helmets, safety glasses, vests)
-                2. Unsafe behaviors or positions
-                3. Equipment and machinery safety
-                4. Environmental hazards
-                Provide specific observations.
-                
-                <image>data:image/jpeg;base64,{img_base64}</image>"""
+                # Minimal prompt
+                prompt = f"""List safety issues: <image>data:image/jpeg;base64,{img_base64}</image>"""
 
                 completion = self.client.chat.completions.create(
                     messages=[
@@ -72,12 +68,12 @@ def create_monitor_interface():
                         }
                     ],
                     model=self.model_name,
-                    max_tokens=200,
-                    temperature=0.2
+                    max_tokens=100,
+                    temperature=0.1
                 )
                 return completion.choices[0].message.content
             except Exception as e:
-                print(f"Detailed error: {str(e)}")  # For debugging
+                print(f"Detailed error: {str(e)}")
                 return f"Analysis Error: {str(e)}"
 
         def process_frame(self, frame: np.ndarray) -> tuple[np.ndarray, str]:
@@ -109,16 +105,13 @@ def create_monitor_interface():
     monitor = SafetyMonitor()
     
     with gr.Blocks() as demo:
-        gr.Markdown("""
-        # Safety Monitoring System
-        Upload an image to analyze workplace safety concerns.
-        """)
+        gr.Markdown("# Safety Analysis System")
         
         with gr.Row():
             input_image = gr.Image(label="Upload Image")
-            output_image = gr.Image(label="Analysis Results")
+            output_image = gr.Image(label="Results")
         
-        analysis_text = gr.Textbox(label="Detailed Safety Analysis", lines=5)
+        analysis_text = gr.Textbox(label="Analysis", lines=5)
             
         def analyze_image(image):
             if image is None:
@@ -127,7 +120,7 @@ def create_monitor_interface():
                 processed_frame, analysis = monitor.process_frame(image)
                 return processed_frame, analysis
             except Exception as e:
-                print(f"Processing error: {str(e)}")  # For debugging
+                print(f"Processing error: {str(e)}")
                 return None, f"Error processing image: {str(e)}"
             
         input_image.change(
@@ -135,13 +128,6 @@ def create_monitor_interface():
             inputs=input_image,
             outputs=[output_image, analysis_text]
         )
-        
-        gr.Markdown("""
-        ## Instructions:
-        1. Upload an image using the input panel
-        2. The system will automatically analyze it for safety concerns
-        3. View the analyzed image with overlay and detailed analysis below
-        """)
 
     return demo