Add AI image upscaler Gradio app

Add a Gradio-based AI image upscaler application (main.py) using Real-ESRGAN with an RRDBNet model and a cached upsampler loader to avoid reloading models on each request. Add project metadata and dependencies in pyproject.toml, a minimal README frontmatter, .gitignore for Python artifacts, and .python-version (3.11). (Note: a lockfile was also added but is not described here.)

.gitignore

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+# Python-generated files
+__pycache__/
+*.py[oc]
+build/
+dist/
+wheels/
+*.egg-info
+
+# Virtual environments
+.venv

.python-version

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+3.11

README.md

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+---
+title: AI Image Upscaler
+emoji: 🔍
+colorFrom: purple
+colorTo: blue
+sdk: gradio
+sdk_version: "4.0"
+app_file: app.py
+pinned: false
+---

main.py

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+import gradio as gr
+import numpy as np
+from PIL import Image
+from realesrgan import RealESRGANer
+from basicsr.archs.rrdbnet_arch import RRDBNet
+
+# Load model once at startup (not on every call)
+def load_model(scale=4):
+    model = RRDBNet(
+        num_in_ch=3, num_out_ch=3,
+        num_feat=64, num_block=23, num_grow_ch=32, scale=scale
+    )
+    upsampler = RealESRGANer(
+        scale=scale,
+        model_path=f"https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x{scale}plus.pth",
+        model=model,
+        half=False  # set True if GPU available
+    )
+    return upsampler
+
+upsampler_cache = {}
+
+def upscale(image: Image.Image, scale: int):
+    if scale not in upsampler_cache:
+        upsampler_cache[scale] = load_model(scale)
+    
+    upsampler = upsampler_cache[scale]
+    img_array = np.array(image)
+    output, _ = upsampler.enhance(img_array, outscale=scale)
+    return Image.fromarray(output)
+
+# Gradio UI
+with gr.Blocks(title="AI Image Upscaler") as demo:
+    gr.Markdown("## 🔍 AI Image Upscaler\nPowered by Real-ESRGAN")
+    
+    with gr.Row():
+        with gr.Column():
+            input_img = gr.Image(type="pil", label="Input Image")
+            scale_choice = gr.Radio(
+                choices=[2, 4, 8], value=4, label="Upscale Factor"
+            )
+            btn = gr.Button("Upscale", variant="primary")
+        
+        with gr.Column():
+            output_img = gr.Image(type="pil", label="Upscaled Output")
+    
+    btn.click(fn=upscale, inputs=[input_img, scale_choice], outputs=output_img)
+
+demo.launch()

pyproject.toml

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+[project]
+name = "image-upscaler"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "basicsr>=1.4.2",
+    "gradio>=6.11.0",
+    "numpy<2",
+    "pillow>=12.2.0",
+    "realesrgan>=0.3.0",
+    "torch==2.1.2",
+    "torchvision==0.16.2",
+]