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app.py

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+from PIL import Image
+import numpy as np
+from rembg import remove
+import cv2
+import os
+from torchvision.transforms import GaussianBlur
+import gradio as gr
+import replicate
+import requests
+from io import BytesIO
+
+def create_mask(input):
+    input_path = 'input.png'
+    bg_removed_path = 'bg_removed.png'
+    mask_name = 'blured_mask.png'
+    
+    input.save(input_path)
+    bg_removed = remove(input)
+    bg_removed = bg_removed.resize((512, 512))
+    bg_removed.save(bg_removed_path)
+
+    img2_grayscale = bg_removed.convert('L')
+    img2_a = np.array(img2_grayscale)
+
+    mask = np.array(img2_grayscale)
+    threshhold = 0
+    mask[img2_a==threshhold] = 1  
+    mask[img2_a>threshhold] = 0 
+
+    strength = 1  
+    d = int(255 * (1-strength))
+    mask *= 255-d 
+    mask += d
+
+    mask = Image.fromarray(mask)
+
+    blur = GaussianBlur(11,20)
+    mask = blur(mask)
+    mask = mask.resize((512, 512))
+
+    mask.save(mask_name)
+
+    return Image.open(mask_name)
+
+
+def generate_image(image, product_name, target_name):
+  mask = create_mask(image)
+  image = image.resize((512, 512))
+  mask = mask.resize((512,512))
+  guidance_scale=16
+  num_samples = 1
+
+  prompt = 'a photo of a ' + product_name + ' with ' + target_name + ' product photograpy'
+  
+  model = replicate.models.get("cjwbw/stable-diffusion-v2-inpainting")
+  version = model.versions.get("f9bb0632bfdceb83196e85521b9b55895f8ff3d1d3b487fd1973210c0eb30bec")
+  output = version.predict(prompt=prompt, image=open("bg_removed.png", "rb"), mask=open("blured_mask.png", "rb"))
+  response = requests.get(output[0])
+
+  return Image.open(BytesIO(response.content))
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Advertise better with AI")
+    # with gr.Tab("Prompt Paint - Basic"):
+    with gr.Row():
+
+      with gr.Column():
+        input_image = gr.Image(label = "Upload your product's photo", type = 'pil')
+
+        product_name = gr.Textbox(label="Describe your product")
+        target_name = gr.Textbox(label="Where do you want to put your product?")
+        # 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, product_name, target_name ], outputs=image_output, api_name='test')
+
+
+demo.launch()

requirements.txt

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+rembg==2.0.30
+torchvision==0.13.1
+numpy==1.23.5
+Pillow==9.3.0
+opencv-python==4.6.0.66
+gradio==3.9.1