add app

app.py

@@ -0,0 +1,73 @@
+from PIL import Image
+import numpy as np
+from rembg import remove
+import cv2
+import os
+from torchvision.transforms import GaussianBlur
+import replicate
+import gradio as gr
+import requests
+
+os.environ["API_TOKEN"]
+
+model = replicate.models.get("cjwbw/stable-diffusion-v2-inpainting")
+version = model.versions.get("f9bb0632bfdceb83196e85521b9b55895f8ff3d1d3b487fd1973210c0eb30bec")
+
+def generate_image(input, prompt):
+  input_path = 'input.png'
+  output_path = 'output.png'
+
+  #input = Image.open(input_path)
+  input = input.resize((512, 512))
+  input.save(input_path)
+  bg_removed = remove(input)
+
+  img2_grayscale = bg_removed.convert('L')
+  img2_a = np.array(img2_grayscale)
+
+  mask = np.array(img2_grayscale)
+  threshhold = 0
+  mask[img2_a==threshhold] = 1  # this is white
+  mask[img2_a>threshhold] = 0 # this is gray
+  #The mask structure is white for inpainting and black for keeping as is
+
+  strength = 1  # This controls the strength of our prompt relative to the init image.
+  seed = 123
+
+  d = int(255 * (1-strength))
+  mask *= 255-d # Converts our range from [0,1] to [0,255]
+  mask += d
+
+  mask = Image.fromarray(mask)
+
+  blur = GaussianBlur(11,20)
+  mask = blur(mask)
+  mask.save("blured_mask.png")
+
+  url = version.predict(prompt=prompt, image=open(input_path,"rb"), mask=open("blured_mask.png","rb"))[0]
+  response = requests.get(url)
+
+  with open('output.png', 'wb') as f:
+      f.write(response.content)
+  
+  return Image.open('output.png')
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Advertise better with AI")
+    with gr.Row():
+
+      with gr.Column():
+        input_image = gr.Image(label = "Upload your product's photo", type = 'pil')
+
+        target_name = gr.Textbox(label="Write your prompt here")
+        # result_prompt = product_name + ' in ' + target_name + 'product photograpy ultrarealist'
+
+        image_button = gr.Button("Generate")
+      
+      with gr.Column():
+        image_output = gr.Image()
+    
+    image_button.click(generate_image, inputs=[input_image, target_name ], outputs=image_output)
+
+
+demo.launch()

requirements.txt

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+rembg 
+replicate