created app.py

app.py

@@ -0,0 +1,35 @@
+import torch
+import gradio as gr
+from diffusers import StableDiffusionControlNetPipeline, ControlNetModel
+from PIL import Image
+
+# Load ControlNet model
+controlnet = ControlNetModel.from_pretrained("lllyasviel/control_v11p_sd15_inpaint", torch_dtype=torch.float16)
+
+# Load Stable Diffusion Pipeline
+pipe = StableDiffusionControlNetPipeline.from_pretrained(
+    "runwayml/stable-diffusion-v1-5",
+    controlnet=controlnet,
+    torch_dtype=torch.float16
+).to("cuda")
+
+# Function to process images
+def remove_filter(image, prompt):
+    output = pipe(prompt=prompt, image=image).images[0]
+    return output
+
+# Gradio Interface
+iface = gr.Interface(
+    fn=remove_filter,
+    inputs=[
+        gr.Image(type="pil"),  # Image input
+        gr.Textbox(label="Custom Prompt", placeholder="Enter a custom prompt", default="restore the original colors and details, remove the filter")  # Textbox for the prompt
+    ],
+    outputs=gr.Image(type="pil"),
+    title="Filter Removal using ControlNet",
+    description="Upload a filtered image and provide a prompt to restore the original image.",
+)
+
+# Launch the app
+if __name__ == "__main__":
+    iface.launch()