Update app.py

app.py

@@ -10,7 +10,7 @@ import torch
 from diffusers import AutoPipelineForImage2Image
 from diffusers.utils import make_image_grid, load_image
 
-
+base_url=f'https://omnibus-top-20-img-img.hf.space/file='
 loaded_model=[]
 for i,model in enumerate(models):
     try:
@@ -20,19 +20,14 @@ for i,model in enumerate(models):
         pass
 print (loaded_model)
 
+pipeline = AutoPipelineForImage2Image.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float32, use_safetensors=True)
 
-def run_dif(out_prompt,model_drop,cnt):
-    out_box=[]
+def load_model(model_drop):
+    pipeline = AutoPipelineForImage2Image.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float32, use_safetensors=True)
 
-    pipeline = AutoPipelineForImage2Image.from_pretrained(
-        "runwayml/stable-diffusion-v1-5", torch_dtype=torch.float32, use_safetensors=True
-    )
-    #pipeline.enable_model_cpu_offload()
-    # remove following line if xFormers is not installed or you have PyTorch 2.0 or higher installed
-    #pipeline.enable_xformers_memory_efficient_attention()
-    
-    # prepare image
-    url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/img2img-init.png"
+def run_dif(prompt,im_path,model_drop,cnt):
+    out_box=[]
+    url = base_url+im_path
     init_image = load_image(url)
     
     prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
@@ -159,13 +154,14 @@ min-width:200px;
 """
 with gr.Blocks(css=css) as app:
     with gr.Row():
-        inp=gr.Textbox(label="Prompt")
-        btn=gr.Button()
-        
+        with gr.Column():
+            inp=gr.Textbox(label="Prompt")
+            btn=gr.Button()
+        inp_im=gr.Image(type='filepath')
     with gr.Row():
         model_drop=gr.Dropdown(label="Models", choices=models, type='index', value=models[0])
         cnt = gr.Number(value=1)
     out_html=gr.HTML()
     outp=gr.Gallery()
-    btn.click(run_dif,[inp,model_drop,cnt],[outp,out_html])
+    btn.click(run_dif,[inp,inp_im,model_drop,cnt],[outp,out_html])
 app.launch()