Add application file

README.md

@@ -1,13 +1,16 @@
 ---
-title: Upscale Api
-emoji: 👁
-colorFrom: red
-colorTo: indigo
-sdk: streamlit
-sdk_version: 1.37.1
+title: Face Real ESRGAN 2x 4x 8x
+emoji: 😻
+colorFrom: green
+colorTo: gray
+sdk: gradio
+sdk_version: 4.41.0
+python_version: 3.11.9
 app_file: app.py
-pinned: false
+pinned: true
 license: apache-2.0
+models:
+- ai-forever/Real-ESRGAN
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference

main.py

@@ -0,0 +1,45 @@
+import torch
+from PIL import Image
+from RealESRGAN import RealESRGAN
+import os
+
+# Function to perform inference and upscale the image
+def upscale_image(image_path, scale):
+ # Initialize device
+ device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+
+ # Initialize and load models
+ model = RealESRGAN(device, scale=scale, weights_only=False) 
+ model.load_weights(f'weights/RealESRGAN_x{scale}.pth', download=True)
+ 
+ # Open the image from the file path
+ try:
+ image = Image.open(image_path)
+ except Exception as e:
+ print(f"Error opening the image: {e}")
+ return
+
+ # Perform inference
+ try:
+ result = model.predict(image.convert('RGB'))
+ except Exception as e:
+ print(f"Error during inference: {e}")
+ return
+
+ # Save the upscaled image
+ output_path = f'upscaled_image_x{scale}.png'
+ result.save(output_path, 'PNG')
+ print(f"Upscaled image saved to {output_path}")
+
+if __name__ == '__main__':
+ # Path of the image to be upscaled
+ image_path = './groot.jpeg'
+ 
+ # Scaling factor (2x, 4x, or 8x)
+ scale = input("Enter the scaling factor (2, 4, or 8): ")
+ 
+ # Validate scale
+ if scale not in ['2', '4', '8']:
+ print("Invalid scale factor. Please enter 2, 4, or 8.")
+ else:
+ upscale_image(image_path, int(scale)) 

requirements.txt

@@ -0,0 +1,4 @@
+git+https://github.com/doevent/Real-ESRGAN.git
+torch
+Pillow
+flask