Update app.py

app.py

@@ -8,8 +8,9 @@ sys.path.append('./taming-transformers')
 sys.path.append('./latent-diffusion')
 from taming.models import vqgan 
 from ldm.util import instantiate_from_config
+from huggingface_hub import hf_hub_download
 
-torch.hub.download_url_to_file('https://ommer-lab.com/files/latent-diffusion/nitro/txt2img-f8-large/model.ckpt','txt2img-f8-large.ckpt')
+model_path_e = hf_hub_download(repo_id="multimodalart/compvis-latent-diffusion-text2img-large", filename="txt2img-f8-large.ckpt")
 
 #@title Import stuff
 import argparse, os, sys, glob
@@ -91,7 +92,7 @@ def is_unsafe(safety_model, embeddings, threshold=0.5):
     return True if x > threshold else False
 
 config = OmegaConf.load("latent-diffusion/configs/latent-diffusion/txt2img-1p4B-eval.yaml")
-model = load_model_from_config(config, f"txt2img-f8-large.ckpt")
+model = load_model_from_config(config,model_path_e)
 device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
 model = model.to(device)
 
@@ -160,7 +161,7 @@ def run(prompt, steps, width, height, images, scale):
                           image_features = clip_model.encode_image(image_preprocess)
                         image_features /= image_features.norm(dim=-1, keepdim=True)
                         query = image_features.cpu().detach().numpy().astype("float32")
-                        #unsafe = is_unsafe(safety_model,query,0.5)
+                        unsafe = is_unsafe(safety_model,query,0.5)
                         unsafe=False
                         if(not unsafe):
                             all_samples_images.append(image_vector)
@@ -195,6 +196,6 @@ iface = gr.Interface(fn=run, inputs=[
     outputs=[image,gr.outputs.Carousel(label="Individual images",components=["image"]),gr.outputs.Textbox(label="Error")],
     css=css,
     title="Generate images from text with Latent Diffusion LAION-400M",
-    description="<div>By typing a prompt and pressing submit you can generate images based on this prompt. <a href='https://github.com/CompVis/latent-diffusion' target='_blank'>Latent Diffusion</a> is a text-to-image model created by <a href='https://github.com/CompVis' target='_blank'>CompVis</a>, trained on the <a href='https://laion.ai/laion-400-open-dataset/'>LAION-400M dataset.</a><br>This UI to the model was assembled by <a style='color: rgb(245, 158, 11);font-weight:bold' href='https://twitter.com/multimodalart' target='_blank'>@multimodalart</a></div>",
+    description="<div>By typing a prompt and pressing submit you can generate images based on this prompt. <a href='https://github.com/CompVis/latent-diffusion' target='_blank'>Latent Diffusion</a> is a text-to-image model created by <a href='https://github.com/CompVis' target='_blank'>CompVis</a>, trained on the <a href='https://laion.ai/laion-400-open-dataset/'>LAION-400M dataset.</a><br>This UI to the model was assembled by <a style='color: rgb(245, 158, 11);font-weight:bold' href='https://twitter.com/multimodalart' target='_blank'>@multimodalart</a> nsfw filter desactivated</div>",
     article="<h4 style='font-size: 110%;margin-top:.5em'>Biases acknowledgment</h4><div>Despite how impressive being able to turn text into image is, beware to the fact that this model may output content that reinforces or exarcbates societal biases. According to the <a href='https://arxiv.org/abs/2112.10752' target='_blank'>Latent Diffusion paper</a>:<i> \"Deep learning modules tend to reproduce or exacerbate biases that are already present in the data\"</i>. The model was trained on an unfiltered version the LAION-400M dataset, which scrapped non-curated image-text-pairs from the internet (the exception being the the removal of illegal content) and is meant to be used for research purposes, such as this one. <a href='https://laion.ai/laion-400-open-dataset/' target='_blank'>You can read more on LAION's website</a></div><h4 style='font-size: 110%;margin-top:1em'>Who owns the images produced by this demo?</h4><div>Definetly not me! Probably you do. I say probably because the Copyright discussion about AI generated art is ongoing. So <a href='https://www.theverge.com/2022/2/21/22944335/us-copyright-office-reject-ai-generated-art-recent-entrance-to-paradise' target='_blank'>it may be the case that everything produced here falls automatically into the public domain</a>. But in any case it is either yours or is in the public domain.</div>")
 iface.launch(enable_queue=True)