Update app.py

app.py

@@ -139,39 +139,37 @@ model_uniformer = None
 #    return [result]
 
 
-model_lineart_anime = None
-
-
-def lineart_anime(img, res, invert=True):
-    img = resize_image(HWC3(img), res)
-    global model_lineart_anime
-    if model_lineart_anime is None:
-        from annotator.lineart_anime import LineartAnimeDetector
-        model_lineart_anime = LineartAnimeDetector()
-#    result = model_lineart_anime(img)
-    if (invert):
-        result = cv2.bitwise_not(model_lineart_anime(img))
-    else:
-        result = model_lineart_anime(img)
-    return [result]
-
 
+model_lineart_anime = None
 model_lineart = None
 
 
-def lineart(img, res, coarse=False, invert=True):
+def lineart(img, res, preprocessor_name=Lineart, invert=True):
     img = resize_image(HWC3(img), res)
-    global model_lineart
-    if model_lineart is None:
-        from annotator.lineart import LineartDetector
-        model_lineart = LineartDetector()
-#    result = model_lineart(img, coarse)
-    if (invert):
-        result = cv2.bitwise_not(model_lineart(img, coarse))
-    else:
-        result = model_lineart(img, coarse)    
-    return [result]
-
+    ["Lineart", "Lineart Coarse", "Lineart Anime"]
+    if preprocessor_name in ["Lineart", "Lineart Coarse"]:
+        coarse = "Coarse" in preprocessor_name
+        global model_lineart
+        if model_lineart is None:
+            from annotator.lineart import LineartDetector
+            model_lineart = LineartDetector()
+    #    result = model_lineart(img, coarse)
+        if (invert):
+            result = cv2.bitwise_not(model_lineart(img, coarse))
+        else:
+            result = model_lineart(img, coarse)    
+        return [result]
+    elif preprocessor_name == "Lineart Anime":
+        global model_lineart_anime
+        if model_lineart_anime is None:
+            from annotator.lineart_anime import LineartAnimeDetector
+            model_lineart_anime = LineartAnimeDetector()
+    #    result = model_lineart_anime(img)
+        if (invert):
+            result = cv2.bitwise_not(model_lineart_anime(img))
+        else:
+            result = model_lineart_anime(img)
+        return [result]
 
 model_oneformer_coco = None
 
@@ -387,39 +385,22 @@ with gr.Blocks(theme=theme) as demo:
     #            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
                 gallery = gr.Gallery(label="Generated images", show_label=False, height="auto")
         run_button.click(fn=openpose, inputs=[input_image, resolution, hand_and_face], outputs=[gallery])
-    
-    with gr.Tab("Lineart Anime"):
-        with gr.Row():
-            gr.Markdown("## Lineart Anime \n<p>Check Invert to use with Mochi Diffusion.")
-        with gr.Row():
-            with gr.Column():
-    #            input_image = gr.Image(source='upload', type="numpy")
-                input_image = gr.Image(label="Input Image", type="numpy", height=512)
-                invert = gr.Checkbox(label='Invert', value=True)
-                resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
-                run_button = gr.Button("Run")
-    #            run_button = gr.Button(label="Run")
-            with gr.Column():
-    #            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
-                gallery = gr.Gallery(label="Generated images", show_label=False, height="auto")
-        run_button.click(fn=lineart_anime, inputs=[input_image, resolution, invert], outputs=[gallery])
+
     
     with gr.Tab("Lineart"):
         with gr.Row():
             gr.Markdown("## Lineart \n<p>Check Invert to use with Mochi Diffusion.  Inverted image can also be created here for use with ControlNet Scribble.")
         with gr.Row():
             with gr.Column():
-    #            input_image = gr.Image(source='upload', type="numpy")
+                preprocessor_name = gr.Radio(label="Preprocessor", choices=["Lineart", "Lineart Coarse", "Lineart Anime"], type="value", value="Lineart")
                 input_image = gr.Image(label="Input Image", type="numpy", height=512)
-                coarse = gr.Checkbox(label='Using coarse model', value=False)
                 invert = gr.Checkbox(label='Invert', value=True)
                 resolution = gr.Slider(label="resolution", minimum=256, maximum=1024, value=512, step=64)
                 run_button = gr.Button("Run")
     #            run_button = gr.Button(label="Run")
             with gr.Column():
-    #            gallery = gr.Gallery(label="Generated images", show_label=False).style(height="auto")
                 gallery = gr.Gallery(label="Generated images", show_label=False, height="auto")
-        run_button.click(fn=lineart, inputs=[input_image, resolution, coarse, invert], outputs=[gallery])
+        run_button.click(fn=lineart, inputs=[input_image, resolution, preprocessor_name, invert], outputs=[gallery])
     
     
     with gr.Tab("InPaint"):
@@ -511,4 +492,4 @@ with gr.Blocks(theme=theme) as demo:
     run_button.click(fn=color_shuffler, inputs=[input_image, resolution], outputs=[gallery])
 
 
-demo.launch()
+demo.launch()