Upload app.py

app.py

@@ -49,15 +49,16 @@ def inference(image_url, image, min_score):
             im = np.frombuffer(r.content, dtype="uint8")
             im = cv2.imdecode(im, cv2.IMREAD_COLOR)
     else:
+        im = cv2.imread(image.name)
         # Model expect BGR!
-        im = image[:,:,::-1]
+        #im = image[:,:,::-1]
 
     cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = min_score
     predictor = DefaultPredictor(cfg)
 
     outputs = predictor(im)
 
-    v = Visualizer(im, my_metadata, scale=1.2, instance_mode=ColorMode.IMAGE )
+    v = Visualizer(im[:,:,::-1], my_metadata, scale=1.2, instance_mode=ColorMode.IMAGE )
     out = v.draw_instance_predictions(outputs["instances"].to("cpu"))
 
     return out.get_image()
@@ -70,7 +71,7 @@ article = '<p>Detectron model is available from our repository <a href="https://
 gr.Interface(
     inference,
     [gr.inputs.Textbox(label="Image URL", placeholder=""),
-     gr.inputs.Image(image_mode="RGB", source="upload", optional=False, label="Input Image"),
+     gr.inputs.Image(type="file", image_mode="RGB", source="upload", optional=False, label="Input Image"),
      gr.Slider(minimum=0.0, maximum=1.0, value=0.5, label="Minimum score"),
     ],
     gr.outputs.Image(type="pil", label="Output"),