Update handler.py

handler.py

@@ -71,36 +71,36 @@ class EndpointHandler:
         pass
 
 
-def __call__(self, image_file):
-    image_array = np.array(image_file)[:, :, ::-1]  # BGR
-    predictions, visualized_output = dense_captioning_demo.run_on_image(image_array)
-    buffer = BytesIO()
-    visualized_output.fig.savefig(buffer, format="png")
-    buffer.seek(0)
-    detections = {}
-    predictions = predictions["instances"].to(torch.device("cpu"))
-
-    for box, description, score in zip(
-        predictions.pred_boxes,
-        predictions.pred_object_descriptions.data,
-        predictions.scores,
-    ):
-        if description not in detections:
-            detections[description] = []
-        detections[description].append(
-            {
-                "xmin": float(box[0]),
-                "ymin": float(box[1]),
-                "xmax": float(box[2]),
-                "ymax": float(box[3]),
-                "score": float(score),
+    def __call__(self, image_file):
+        image_array = np.array(image_file)[:, :, ::-1]  # BGR
+        predictions, visualized_output = dense_captioning_demo.run_on_image(image_array)
+        buffer = BytesIO()
+        visualized_output.fig.savefig(buffer, format="png")
+        buffer.seek(0)
+        detections = {}
+        predictions = predictions["instances"].to(torch.device("cpu"))
+    
+        for box, description, score in zip(
+            predictions.pred_boxes,
+            predictions.pred_object_descriptions.data,
+            predictions.scores,
+        ):
+            if description not in detections:
+                detections[description] = []
+            detections[description].append(
+                {
+                    "xmin": float(box[0]),
+                    "ymin": float(box[1]),
+                    "xmax": float(box[2]),
+                    "ymax": float(box[3]),
+                    "score": float(score),
+                }
+            )
+    
+        output = {
+            "dense_captioning_results": {
+                "detections": detections,
             }
-        )
-
-    output = {
-        "dense_captioning_results": {
-            "detections": detections,
         }
-    }
-
-    return Image.open(buffer), output
+    
+        return Image.open(buffer), output