First model version

app.py

@@ -51,13 +51,19 @@ def infer(filepath):
     cv2.imwrite('result.jpg', visual_image)
     return 'result.jpg', pd.DataFrame(result_words)
 
+description = gr.Markdown('''## Step 1 (Preprocess Input Image)
+- Drop an image containing a near-frontal face to the **Input Image**.
+    - If there are multiple faces in the image, hit the Edit button in the upper right corner and crop the input image beforehand.
+- Hit the **Detect & Align Face** button.
+- Hit the **Reconstruct Face** button.
+    - The final result will be based on this **Reconstructed Face**. So, if the reconstructed image is not satisfactory, you may want to change the input image.
+''')
 
 iface = gr.Interface(
     fn=infer,
     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",
+    description=description,
     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=['figs/test/CANDY.png', 'figs/test/ESPLANADE.png', 'figs/test/KAPPA.png'],
-    #article="<a href=\"https://github.com/MhLiao/MaskTextSpotterV3\">GitHub Repo</a>",
 ).launch(enable_queue=True, cache_examples=True)