Update app.py

app.py

@@ -1,29 +1,65 @@
+# import gradio as gr
+# import torch
+# from diffusers import AutoPipelineForImage2Image
+# from diffusers.utils import make_image_grid, load_image
+
+# # gr.load("models/NSTiwari/SDXL_LoRA_model").launch()
+
+# pipeline = AutoPipelineForImage2Image.from_pretrained(
+#     "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True
+# )
+# pipeline.load_lora_weights('pytorch_lora_weights_00.safetensors')
+# # _ = pipeline.to("cuda")
+
+# pipeline.enable_model_cpu_offload()
+
+# url = "https://img.onmanorama.com/content/dam/mm/en/lifestyle/decor/images/2020/12/1/25-lakh-living-hall.jpg.transform/576x300/image.jpg"
+# # init_image = load_image(url)
+# # image = init_image.resize((1024, 576))
+
+# prompt = "A cozy Indian living room glows with morning sunshine on Republic Day, its walls decked in saffron, white, and green tapestries and art, while colorful cushions and festive garlands add a vibrant, celebratory air."
+
+# # pass prompt and image to pipeline
+# image_out = pipeline(prompt, image=image, strength=0.5).images[0]
+# # make_image_grid([image, image_out], rows=1, cols=2)
+
+
+# # Define the image generation function
+# def generate_image(prompt, image_url):
+#     init_image = load_image(image_url)
+#     image = init_image.resize((1024, 576))
+#     image_out = pipeline(prompt, image=image, strength=0.5).images[0]
+#     return image_out
+
+    
+# # Set up Gradio interface
+# iface = gr.Interface(
+#     fn=generate_image, 
+#     inputs=[gr.Textbox(label="Prompt"), gr.Textbox(label="Image URL")], 
+#     outputs="image"
+# )
+
+# # Launch the Gradio app
+# iface.launch()
+
+
+
+###New###########
+
+
 import gradio as gr
 import torch
 from diffusers import AutoPipelineForImage2Image
-from diffusers.utils import make_image_grid, load_image
-
-# gr.load("models/NSTiwari/SDXL_LoRA_model").launch()
+from diffusers.utils import load_image
 
+# Load the Stable Diffusion pipeline
 pipeline = AutoPipelineForImage2Image.from_pretrained(
     "stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, variant="fp16", use_safetensors=True
 )
 pipeline.load_lora_weights('pytorch_lora_weights_00.safetensors')
-# _ = pipeline.to("cuda")
-
+_ = pipeline.to("cuda")
 pipeline.enable_model_cpu_offload()
 
-url = "https://img.onmanorama.com/content/dam/mm/en/lifestyle/decor/images/2020/12/1/25-lakh-living-hall.jpg.transform/576x300/image.jpg"
-# init_image = load_image(url)
-# image = init_image.resize((1024, 576))
-
-prompt = "A cozy Indian living room glows with morning sunshine on Republic Day, its walls decked in saffron, white, and green tapestries and art, while colorful cushions and festive garlands add a vibrant, celebratory air."
-
-# pass prompt and image to pipeline
-image_out = pipeline(prompt, image=image, strength=0.5).images[0]
-# make_image_grid([image, image_out], rows=1, cols=2)
-
-
 # Define the image generation function
 def generate_image(prompt, image_url):
     init_image = load_image(image_url)
@@ -31,7 +67,6 @@ def generate_image(prompt, image_url):
     image_out = pipeline(prompt, image=image, strength=0.5).images[0]
     return image_out
 
-    
 # Set up Gradio interface
 iface = gr.Interface(
     fn=generate_image, 
@@ -40,4 +75,4 @@ iface = gr.Interface(
 )
 
 # Launch the Gradio app
-iface.launch()
+iface.launch()