1

app.py

@@ -6,9 +6,9 @@ from omegaconf import OmegaConf
 import sys 
 sys.path.append(".")
 sys.path.append('./taming-transformers')
-sys.path.append('./latent-diffusion')
+#sys.path.append('./latent-diffusion')
 from taming.models import vqgan 
-from ldm.util import instantiate_from_config
+from util import instantiate_from_config
 from huggingface_hub import hf_hub_download
 
 model_path_e = hf_hub_download(repo_id="multimodalart/compvis-latent-diffusion-text2img-large", filename="txt2img-f8-large.ckpt")
@@ -92,7 +92,7 @@ def is_unsafe(safety_model, embeddings, threshold=0.5):
     x = np.array([e[0] for e in nsfw_values])
     return True if x > threshold else False
 
-config = OmegaConf.load("latent-diffusion/configs/latent-diffusion/txt2img-1p4B-eval.yaml")
+config = OmegaConf.load("./txt2img-1p4B-eval.yaml")
 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)
@@ -105,7 +105,7 @@ clip_model, _, preprocess = open_clip.create_model_and_transforms('ViT-B-32', pr
 def run(prompt, steps, width, height, images, scale):
     opt = argparse.Namespace(
         prompt = prompt, 
-        outdir='latent-diffusion/outputs',
+        outdir='./outputs',
         ddim_steps = int(steps),
         ddim_eta = 0,
         n_iter = 1,