update app.py

app.py

@@ -34,7 +34,7 @@ textdet_model_list = ['DBNet', 'DRRG', 'FCENet', 'PANet', 'PSENet', 'TextSnake',
 textrec_model_list = ['ABINet', 'ASTER', 'CRNN', 'MASTER', 'NRTR', 'RobustScanner', 'SARNet', 'SATRN', 'SVTR']
 textkie_model_list = ['SDMGR']
 
-def ocr_inference(inputs, out_dir, det, det_weights, rec, rec_weights, kie, kie_weights, device, batch_size):
+def ocr_inference(inputs, out_dir, det, det_weights, rec, rec_weights, kie, kie_weights, device):
     init_args, call_args = parse_args()
     inputs = np.array(inputs)
     img_path = "demo_text_ocr.jpg"
@@ -51,7 +51,7 @@ def ocr_inference(inputs, out_dir, det, det_weights, rec, rec_weights, kie, kie_
         init_args['rec_weights'] = rec_weights
     call_args['inputs'] = img_path
     call_args['out_dir'] = out_dir
-    call_args['batch_size'] = int(batch_size)
+    call_args['batch_size'] = 1
     call_args['show'] = False
     call_args['save_pred'] = True
     call_args['save_vis'] = True
@@ -184,11 +184,11 @@ if __name__ == '__main__':
     output_image = gr.outputs.Image(type="pil", label="Output Image")
     output_json = gr.outputs.Textbox()
     download_test_image()
-    examples = [["demo_text_ocr.jpg", "results", "DBNet", None, "CRNN", "cpu", 1],
-                ["demo_text_det.jpg", "results", "FCENet", None, "ASTER", "cpu", 1],
-                ["demo_text_recog.jpg", "results", "PANet", None, "MASTER", "cpu", 1],
-                ["demo_densetext_det.jpg", "results", "PSENet", None, "CRNN", None, "cpu", 1],
-                ["demo_kie.jpg", "results", "TextSnake", None, "RobustScanner", None, "cpu", 1]
+    examples = [["demo_text_ocr.jpg", "results", "DBNet", None, "CRNN", "cpu"],
+                ["demo_text_det.jpg", "results", "FCENet", None, "ASTER", "cpu"],
+                ["demo_text_recog.jpg", "results", "PANet", None, "MASTER", "cpu"],
+                ["demo_densetext_det.jpg", "results", "PSENet", None, "CRNN", None, "cpu"],
+                ["demo_kie.jpg", "results", "TextSnake", None, "RobustScanner", None, "cpu"]
                 ]
 
     title = "MMOCR web demo"
@@ -202,7 +202,7 @@ if __name__ == '__main__':
     iface = gr.Interface(
         fn=ocr_inference,
         inputs=[
-            input_image, out_dir, det, det_weights, rec, rec_weights, device, batch_size
+            input_image, out_dir, det, det_weights, rec, rec_weights, device
         ],
         outputs=[output_image, output_json], examples=examples,
         title=title, description=description, article=article,