Fix min_confidence not getting passed to process. Add missing requirements.

app.py

@@ -21,7 +21,7 @@ model = model.cuda()
 ddim_sampler = DDIMSampler(model)  # ControlNet _only_ works with DDIM.
 
 
-def process(input_image: Image.Image, prompt, a_prompt, n_prompt, max_faces, min_confidence, num_samples, ddim_steps, guess_mode, strength, scale, seed, eta):
+def process(input_image: Image.Image, prompt, a_prompt, n_prompt, max_faces: int, min_confidence: float, num_samples, ddim_steps, guess_mode, strength, scale, seed: int, eta):
     with torch.no_grad():
         empty = generate_annotation(input_image, max_faces, min_confidence)
         visualization = Image.fromarray(empty)  # Save to help debug.
@@ -98,7 +98,7 @@ with block:
                                       value='longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality')
         with gr.Column():
             result_gallery = gr.Gallery(label='Output', show_label=False, elem_id="gallery").style(grid=2, height='auto')
-    ips = [input_image, prompt, a_prompt, n_prompt, max_faces, num_samples, ddim_steps, guess_mode, strength, scale, seed, eta]
+    ips = [input_image, prompt, a_prompt, n_prompt, max_faces, min_confidence, num_samples, ddim_steps, guess_mode, strength, scale, seed, eta]
     run_button.click(fn=process, inputs=ips, outputs=[result_gallery])
 
 

requirements.txt

@@ -1,6 +1,13 @@
+einops
+gradio
 huggingface_hub==0.13.3
-mediapipe
+mediapipe==0.9.1.0
 numpy
-pillow
-torch
-tqdm
+omegaconf
+Pillow==9.4.0
+pytorch-lightning==1.9.3
+timm
+transformers==4.26.1
+torch==1.13.1
+torchvision==0.14.1
+tqdm==4.64.1