Update app.py

app.py

@@ -2,7 +2,6 @@ import torch
 import spaces
 from diffusers import StableDiffusionPipeline, DDIMScheduler, AutoencoderKL
 from transformers import AutoFeatureExtractor
-from diffusers.pipelines.stable_diffusion.safety_checker import StableDiffusionSafetyChecker
 from ip_adapter.ip_adapter_faceid import IPAdapterFaceID, IPAdapterFaceIDPlus
 from huggingface_hub import hf_hub_download
 from insightface.app import FaceAnalysis
@@ -16,10 +15,6 @@ image_encoder_path = "laion/CLIP-ViT-H-14-laion2B-s32B-b79K"
 ip_ckpt = hf_hub_download(repo_id="h94/IP-Adapter-FaceID", filename="ip-adapter-faceid_sd15.bin", repo_type="model")
 ip_plus_ckpt = hf_hub_download(repo_id="h94/IP-Adapter-FaceID", filename="ip-adapter-faceid-plusv2_sd15.bin", repo_type="model")
 
-safety_model_id = "CompVis/stable-diffusion-safety-checker"
-safety_feature_extractor = AutoFeatureExtractor.from_pretrained(safety_model_id)
-safety_checker = StableDiffusionSafetyChecker.from_pretrained(safety_model_id)
-
 device = "cuda"
 
 noise_scheduler = DDIMScheduler(
@@ -36,14 +31,10 @@ pipe = StableDiffusionPipeline.from_pretrained(
     base_model_path,
     torch_dtype=torch.float16,
     scheduler=noise_scheduler,
-    vae=vae,
-    feature_extractor=safety_feature_extractor,
-    safety_checker=safety_checker
+    vae=vae
+    # Removed feature_extractor and safety_checker
 ).to(device)
 
-#pipe.load_lora_weights("h94/IP-Adapter-FaceID", weight_name="ip-adapter-faceid-plusv2_sd15_lora.safetensors")
-#pipe.fuse_lora()
-
 ip_model = IPAdapterFaceID(pipe, ip_ckpt, device)
 ip_model_plus = IPAdapterFaceIDPlus(pipe, image_encoder_path, ip_plus_ckpt, device)
 
@@ -134,4 +125,4 @@ with gr.Blocks(css=css) as demo:
     
     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.")
     
-demo.launch()
+demo.launch()