Update app.py

app.py

@@ -10,7 +10,7 @@ import sys
 from diffusers.utils import load_image
 from diffusers import EulerDiscreteScheduler, T2IAdapter
 
-from huggingface_hub import hf_hub_download, login
+from huggingface_hub import snapshot_download, hf_hub_download, login
 import gradio as gr
 
 from pipeline_t2i_adapter import PhotoMakerStableDiffusionXLAdapterPipeline
@@ -23,8 +23,17 @@ from aspect_ratio_template import aspect_ratios
 HF_TOKEN = os.environ.get("HF_TOKEN", None)
 login(HF_TOKEN)
 # global variable
-base_model_path = 'RunDiffusion/Juggernaut-XI-v11'
-# base_model_path = 'SG161222/RealVisXL_V5.0_Lightning'
+
+# model_id = 'SG161222/RealVisXL_V5.0'
+# model_id = 'Lykon/dreamshaper-xl-lightning'
+# model_id = 'SG161222/RealVisXL_V5.0_Lightning'
+model_id = 'RunDiffusion/Juggernaut-XI-v11'
+base_model_path = Path(model_id)
+os.makedirs(base_model_path, exist_ok=True)
+snapshot_download(repo_id=model_id, local_dir=base_model_path)
+
+# base_model_path = 
+# base_model_path = 
 face_detector = FaceAnalysis2(providers=['CPUExecutionProvider', 'CUDAExecutionProvider'], allowed_modules=['detection', 'recognition'])
 face_detector.prepare(ctx_id=0, det_size=(640, 640))
 
@@ -375,7 +384,7 @@ with gr.Blocks(css=css) as demo:
                 num_outputs = gr.Slider(
                     label="Number of output images",
                     minimum=1,
-                    maximum=12,
+                    maximum=18,
                     step=1,
                     value=2,
                 )