First model version

app.py

@@ -48,7 +48,7 @@ def infer(filepath):
     visual_image = det_demo.visualization(image.copy(), result_polygons, result_masks, result_boxes, result_words)
     
     cv2.imwrite('result.jpg', visual_image)
-    return 'result.jpg'#, pd.DataFrame(result_words)
+    return 'result.jpg', pd.DataFrame(result_words)
 
 
 iface = gr.Interface(
@@ -56,7 +56,7 @@ iface = gr.Interface(
     title="张博强毕设展示",
     description="毕设题目：自然场景中任意形状文字的检测与识别\n目前进度：检测",
     inputs=[gr.inputs.Image(label="image", type="filepath")],
-    outputs=[gr.outputs.Image()], #, gr.outputs.Dataframe(headers=['word'])],
+    outputs=[gr.outputs.Image(), gr.outputs.Dataframe(headers=['word'])], 
     #examples=['example1.jpg', 'example2.jpg', 'example3.jpg'],
     #article="<a href=\"https://github.com/MhLiao/MaskTextSpotterV3\">GitHub Repo</a>",
 ).launch(enable_queue=True)

det_demo.py

@@ -580,7 +580,7 @@ class DetDemo(object):
         green[...,2] = 0
         for mask, word, box in zip(masks, words, boxes):
             image[mask] = image[mask] * 0.5 + green[mask] * 0.5
-            cv2.putText(image, word, (box[0], box[1]), cv2.FONT_HERSHEY_COMPLEX, 1, (0,0,255), 2)
+            cv2.putText(image, word, (box[0], box[1]), cv2.FONT_HERSHEY_COMPLEX, 0.4, (0,0,255), 2)
         '''
         for box in boxes:
             cv2.rectangle(image,(box[0], box[1]), (box[2], box[3]), (0,0,255), 2)