Update app.py

app.py

@@ -47,7 +47,7 @@ ip_model = IPAdapterInstruct(pipe, image_encoder_path, ip_ckpt, device,dtypein=t
 cv2.setNumThreads(1)
 
 @spaces.GPU(enable_queue=True)
-def generate_image(images, prompt, negative_prompt, preserve_face_structure, face_strength, scale, nfaa_negative_prompt, progress=gr.Progress(track_tqdm=True)):
+def generate_image(images, prompt, negative_prompt, scale, nfaa_negative_prompt, progress=gr.Progress(track_tqdm=True)):
     faceid_all_embeds = []
     first_iteration = True
     image = images[0]
@@ -59,7 +59,7 @@ def generate_image(images, prompt, negative_prompt, preserve_face_structure, fac
     print("Generating normal")
     image = ip_model.generate(
         prompt=prompt, negative_prompt=total_negative_prompt, pil_image=image,
-        scale=scale, width=512, height=512, num_inference_steps=30
+        scale=scale, width=512, height=512, num_inference_steps=30,query="use everything from the image"
     )
 
     print(image)
@@ -95,22 +95,15 @@ with gr.Blocks(css=css) as demo:
                        info="Try something like 'a photo of a man/woman/person'",
                        placeholder="A photo of a [man/woman/person]...")
             negative_prompt = gr.Textbox(label="Negative Prompt", placeholder="low quality")
-            style = gr.Radio(label="Generation type", info="For stylized try prompts like 'a watercolor painting of a woman'", choices=["Photorealistic", "Stylized"], value="Photorealistic")
             submit = gr.Button("Submit")
             with gr.Accordion(open=False, label="Advanced Options"):
-                preserve = gr.Checkbox(label="Preserve Face Structure", info="Higher quality, less versatility (the face structure of your first photo will be preserved). Unchecking this will use the v1 model.", value=True)
-                face_strength = gr.Slider(label="Face Structure strength", info="Only applied if preserve face structure is checked", value=1.3, step=0.1, minimum=0, maximum=3)
-                scale = gr.Slider(label="Scale", value=1.0, step=0.1, minimum=0, maximum=5)
                 nfaa_negative_prompts = gr.Textbox(label="Appended Negative Prompts", info="Negative prompts to steer generations towards safe for all audiences outputs", value="naked, bikini, skimpy, scanty, bare skin, lingerie, swimsuit, exposed, see-through")    
         with gr.Column():
             gallery = gr.Gallery(label="Generated Images")
-        style.change(fn=change_style,
-                    inputs=style,
-                    outputs=[preserve, face_strength, scale])
         files.upload(fn=swap_to_gallery, inputs=files, outputs=[uploaded_files, clear_button, files])
         remove_and_reupload.click(fn=remove_back_to_files, outputs=[uploaded_files, clear_button, files])
         submit.click(fn=generate_image,
-                    inputs=[files,prompt,negative_prompt,preserve, face_strength, scale, nfaa_negative_prompts],
+                    inputs=[files,prompt,negative_prompt, scale, nfaa_negative_prompts],
                     outputs=gallery)
     
     gr.Markdown("This demo includes extra features to mitigate the implicit bias of the model and prevent explicit usage of it to generate content with faces of people, including third parties, that is not safe for all audiences, including naked or semi-naked people.")