Duplicate from kadirnar/bsrgan

Co-authored-by: Kadir Nar <kadirnar@users.noreply.huggingface.co>

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README.md

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+---
+title: Bsrgan
+emoji: 🔥
+colorFrom: purple
+colorTo: indigo
+sdk: gradio
+sdk_version: 3.14.0
+app_file: app.py
+pinned: false
+license: apache-2.0
+tags:
+- making-demos
+duplicated_from: kadirnar/bsrgan
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import torch
+from bsrgan import BSRGAN
+
+# Images
+torch.hub.download_url_to_file('https://raw.githubusercontent.com/kadirnar/bsrgan-pip/main/data/images/butterfly.png', 'butterfly.jpg')
+
+def bsrgan_inference(
+    image: gr.inputs.Image = None,
+    model_path: gr.inputs.Dropdown = 'kadirnar/bsrgan',
+):
+    """
+    BSRGAN inference function
+    Args:
+        image: Input image
+        model_path: Path to the model
+    Returns:
+        Rendered image
+    """
+    device = 'cuda:0' if torch.cuda.is_available() else 'cpu'
+    model = BSRGAN(model_path, device=device, hf_model=True)
+    pred = model.predict(img_path=image)
+    return pred
+        
+
+inputs = [
+    gr.inputs.Image(type="filepath", label="Input Image"),
+    gr.inputs.Dropdown(
+        label="Model",
+        choices=[
+        "kadirnar/bsrgan",
+        "kadirnar/BSRGANx2",
+        "kadirnar/RRDB_PSNR_x4",
+        "kadirnar/RRDB_ESRGAN_x4",
+        "kadirnar/DF2K",
+        "kadirnar/DPED",
+        "kadirnar/DF2K_JPEG",
+        ],
+        default="kadirnar/bsrgan",
+    ),
+]
+
+outputs = gr.outputs.Image(type="filepath", label="Output Image")
+title = "BSRGAN: Designing a Practical Degradation Model for Deep Blind Image Super-Resolution."
+description = "BSRGAN for Deep Blind Image Super-Resolution model aims to design a practical degradation model for deep blind image super-resolution by considering the deterioration of image quality over time. It uses deep learning methods to predict the deterioration of image quality and to assist in the re-creation of images at higher resolution using these predictions."
+examples = [["butterfly.jpg", "kadirnar/bsrgan"]]
+
+demo_app = gr.Interface(
+    fn=bsrgan_inference,
+    inputs=inputs,
+    outputs=outputs,
+    title=title,
+    description=description,
+    examples=examples,
+    cache_examples=True,
+    live=True,
+    theme='huggingface',
+)
+demo_app.launch(debug=True, enable_queue=True)

requirements.txt

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+torch
+bsrgan==0.1.5