| import gradio as gr |
| import numpy as np |
| import cv2 |
| import os |
| import requests |
| import sys |
| from PIL import Image |
|
|
| |
| import torchvision.transforms.functional |
| sys.modules['torchvision.transforms.functional_tensor'] = torchvision.transforms.functional |
|
|
| |
| MODEL_PATH = "RealESRGAN_x4plus.pth" |
|
|
| if not os.path.exists(MODEL_PATH): |
| print("মডেল ডাউনলোড হচ্ছে...") |
| r = requests.get("https://github.com/xinntao/Real-ESRGAN/releases/download/v0.1.0/RealESRGAN_x4plus.pth", stream=True) |
| with open(MODEL_PATH, "wb") as f: |
| for chunk in r.iter_content(chunk_size=8192): |
| f.write(chunk) |
|
|
| from basicsr.archs.rrdbnet_arch import RRDBNet |
| from realesrgan import RealESRGANer |
|
|
| model = RRDBNet(num_in_ch=3, num_out_ch=3, num_feat=64, num_block=23, num_grow_ch=32, scale=4) |
| upsampler = RealESRGANer(scale=4, model_path=MODEL_PATH, model=model, tile=128, tile_pad=10, pre_pad=0, half=False) |
|
|
| |
| def process_image(img): |
| if img is None: |
| return None, None |
| |
| |
| img_np = np.array(img.convert("RGB")) |
| img_bgr = cv2.cvtColor(img_np, cv2.COLOR_RGB2BGR) |
| |
| |
| output_bgr, _ = upsampler.enhance(img_bgr, outscale=4) |
| |
| |
| output_rgb = cv2.cvtColor(output_bgr, cv2.COLOR_BGR2RGB) |
| out_img = Image.fromarray(output_rgb) |
| |
| |
| if out_img.size != (3840, 2160): |
| out_img = out_img.resize((3840, 2160), Image.LANCZOS) |
| |
| |
| out_path = "/tmp/output.png" |
| out_img.save(out_path, "PNG") |
| |
| return out_img, out_path |
|
|
| |
| with gr.Blocks() as demo: |
| gr.Markdown("# 🚀 4K AI Upscaler (Basic Version)") |
| gr.Markdown("সব ডিজাইন বাদ দেওয়া হয়েছে। শুধু ছবি আপলোড করুন এবং রেজাল্ট নিন।") |
| |
| with gr.Row(): |
| inp = gr.Image(type="pil", label="ছবি আপলোড করুন") |
| out = gr.Image(type="pil", label="4K আউটপুট") |
| |
| btn = gr.Button("✨ 4K তে রূপান্তর করুন", variant="primary") |
| file_out = gr.File(label="4K ছবি ডাউনলোড করুন") |
| |
| btn.click(fn=process_image, inputs=inp, outputs=[out, file_out]) |
|
|
| if __name__ == "__main__": |
| demo.queue().launch() |
|
|