Update app.py

app.py

@@ -141,14 +141,14 @@ def plex(mput, prompt, neg_prompt, stips, modal_id, dula, blip, blop):
     cannyimage = np.concatenate([cannyimage, cannyimage, cannyimage], axis=2)
     canny_image = Image.fromarray(cannyimage)
     canny_image.save('./can.png', 'PNG')
-    ##pose_image = load_image(mput)
-    ##pose_image.save('./pos.png', 'PNG')
+    pose_image = load_image(mput)
+    pose_image.save('./pos.png', 'PNG')
     openpose_image = openpose(mput)
     openpose_image.save('./fin.png','PNG')
     images = [openpose_image, canny_image]
 
-    imoge = pipe(prompt,images,num_inference_steps=stips,negative_prompt=neg_prompt,controlnet_conditioning_scale=[blip, blop],height=512,width=512,generator=generator).images[0]
-    return imoge
+    image = pipe(prompt,images,num_inference_steps=stips,negative_prompt=neg_prompt,controlnet_conditioning_scale=[blip, blop],height=512,width=512,generator=generator).images[0]
+    return image
 
-iface = gr.Interface(fn=plex,inputs=[gr.Image(type="filepath"), gr.Textbox(label="prompt"), gr.Textbox(label="neg_prompt", value="monochrome, lowres, bad anatomy, worst quality, low quality"), gr.Slider(label="infer_steps", value=20, minimum=1, step=1, maximum=100), gr.Dropdown(choices=models, value=models[0], type="value", label="select a model"), gr.Dropdown(choices=sdulers, value=sdulers[0], type="value", label="schedulrs"), gr.Slider(label="condition_scale_canny", value=0.5, minimum=0.1, step=0.1, maximum=1), gr.Slider(label="condition_scale_pose", value=0.5, minimum=0.1, step=0.1, maximum=1)], outputs=gr.Image(), title="Img2Img Guided Multi-Conditioned Canny/Pose Controlnet Selectable StableDiffusion Model Demo", description="by JoPmt.")
+iface = gr.Interface(fn=plex,inputs=[gr.Image(type="pil"), gr.Textbox(label="prompt"), gr.Textbox(label="neg_prompt", value="monochrome, lowres, bad anatomy, worst quality, low quality"), gr.Slider(label="infer_steps", value=20, minimum=1, step=1, maximum=100), gr.Dropdown(choices=models, value=models[0], type="value", label="select a model"), gr.Dropdown(choices=sdulers, value=sdulers[0], type="value", label="schedulrs"), gr.Slider(label="condition_scale_canny", value=0.5, minimum=0.1, step=0.1, maximum=1), gr.Slider(label="condition_scale_pose", value=0.5, minimum=0.1, step=0.1, maximum=1)], outputs=gr.Image(), title="Img2Img Guided Multi-Conditioned Canny/Pose Controlnet Selectable StableDiffusion Model Demo", description="by JoPmt.")
 iface.launch()