return image

app.py

@@ -35,10 +35,11 @@ def predict(img: np.ndarray) -> str:
     boxes = boxes[~np.all(boxes == 0, axis=1)]
 
     result = convert_result_to_image(image, resized_image, boxes, conf_labels=False)
-      
-    plt.figure(figsize=(10, 6))
-    plt.axis("off")
-    plt.imshow(result)
+    
+    #plt.figure(figsize=(10, 6))
+    #plt.axis("off")
+    #plt.imshow(result)
+    return result
 
 
 # For each detection, the description is in the [x_min, y_min, x_max, y_max, conf] format:
@@ -92,7 +93,7 @@ def convert_result_to_image(bgr_image, resized_image, boxes, threshold=0.3, conf
 ##### 
 
 title = "Text Detection"
-description = "Image Detection with OpenVino model"
+description = "Text Detection with OpenVino model"
 examples = ['test.jpg']
 interpretation='default'
 enable_queue=True