Update app.py

app.py

@@ -14,8 +14,9 @@ app = Flask(__name__)
 processor = CLIPSegProcessor.from_pretrained("CIDAS/clipseg-rd64-refined")
 model = CLIPSegForImageSegmentation.from_pretrained("CIDAS/clipseg-rd64-refined")
 
-# Global variable for caching results
-cache = {}
+@app.route('/')
+def hello_world():
+    return 'Hello, World!'
 
 # Function to process image and generate mask
 def process_image(image, prompt):
@@ -50,36 +51,7 @@ def get_masks(prompts, img, threshold):
 
     return masks
 
-# Function to extract image using positive and negative prompts
-def extract_image(pos_prompts, neg_prompts, img, threshold):
-    cache_key = (pos_prompts, neg_prompts, threshold)
-    
-    if cache_key in cache:
-        return cache[cache_key]
-
-    positive_masks = get_masks(pos_prompts, img, 0.5)
-    negative_masks = get_masks(neg_prompts, img, 0.5)
-
-    pos_mask = np.any(np.stack(positive_masks), axis=0)
-    neg_mask = np.any(np.stack(negative_masks), axis=0)
-    final_mask = pos_mask & ~neg_mask
-
-    final_mask = Image.fromarray(final_mask.astype(np.uint8) * 255, "L")
-
-    # Convert final mask to base64
-    buffered = io.BytesIO()
-    final_mask.save(buffered, format="PNG")
-    final_mask_base64 = base64.b64encode(buffered.getvalue()).decode("utf-8")
-
-    # Cache the result
-    cache[cache_key] = {'final_mask_base64': final_mask_base64}
-
-    return cache[cache_key]
-
-@app.route('/')
-def hello_world():
-    return 'Hello, World!'
-
+# Route for processing requests
 @app.route('/api', methods=['POST'])
 def process_request():
     data = request.json
@@ -94,10 +66,22 @@ def process_request():
     neg_prompts = data.get('negative_prompts', '')
     threshold = float(data.get('threshold', 0.4))
 
-    # Perform image segmentation
-    result = extract_image(pos_prompts, neg_prompts, img, threshold)
+    # Perform image segmentation without caching
+    positive_masks = get_masks(pos_prompts, img, 0.5)
+    negative_masks = get_masks(neg_prompts, img, 0.5)
+
+    pos_mask = np.any(np.stack(positive_masks), axis=0)
+    neg_mask = np.any(np.stack(negative_masks), axis=0)
+    final_mask = pos_mask & ~neg_mask
+
+    final_mask = Image.fromarray(final_mask.astype(np.uint8) * 255, "L")
+
+    # Convert final mask to base64
+    buffered = io.BytesIO()
+    final_mask.save(buffered, format="PNG")
+    final_mask_base64 = base64.b64encode(buffered.getvalue()).decode("utf-8")
 
-    return jsonify(result)
+    return jsonify({'final_mask_base64': final_mask_base64})
 
 # Keep the server alive using a periodic task
 def keep_alive():