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.gitattributes

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+demo.png filter=lfs diff=lfs merge=lfs -text

.gitignore

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+# Ignore Python bytecode files
+__pycache__/
+*.py[cod]
+
+# Ignore virtual environments
+venv/
+.venv/
+
+# Ignore API keys and configuration files
+.env
+
+# Ignore model files and other large files
+model/
+
+

LICENSE

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+MIT License
+
+Copyright (c) 2025 Salman Alfarisi
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+

README.md

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+---
+title: Real-ESRGAN Dual-Mode Image Upscaler
+emoji: 🖼️
+colorFrom: blue
+colorTo: green
+sdk: gradio
+sdk_version: 5.31.0
+app_file: app.py
+pinned: false
+license: mit
+---
+
+# 🖼️ Real-ESRGAN Dual-Mode Image Upscaler
+
+A lightweight Gradio web app to upscale any image using the Real-ESRGAN model. Simply upload your photo, choose either **Standard Upscale** (×4) or **Premium Upscale** (×8), and download the upscaled image.
+
+
+---
+
+## 📑 Table of Contents
+
+1. [Features](#features)  
+2. [Project Structure](#project-structure)  
+3. [Prerequisites](#prerequisites)  
+4. [Installation](#installation)  
+5. [Running Locally](#running-locally)  
+6. [Usage](#usage)  
+7. [Contributing](#contributing)  
+8. [License](#license)  
+9. [Author & Credits](#author--credits)
+
+---
+
+## ✨ Features
+
+- **Standard Upscale (×4)**  
+  Enhance image resolution by 4x for clearer and larger images.
+
+- **Premium Upscale (×8)**  
+  Upscales first to 4x and then resizes using bicubic interpolation for even higher resolution (8x).
+
+- **Live Preview**  
+  See your original and upscaled images side by side before downloading.
+
+- **Instant Download**  
+  Export the upscaled image as a PNG and use it immediately.
+
+
+
+---
+
+
+## 📁 Project Structure
+
+```
+upscale-project/
+├── model/
+│ └── Real-ESRGAN-x4plus.onnx # ONNX model for upscaling
+├── app.py # Main application file
+├── requirements.txt # List of Python dependencies
+├── .gitignore # Git ignore file to exclude unnecessary files
+├── LICENSE # License file for the project
+└── README.md # Project documentation
+```
+
+---
+
+
+---
+
+## ⚙️ Prerequisites
+
+- Python 3.10 or higher  
+- `git`  
+- A terminal / command prompt  
+
+---
+
+## 🔧 Installation
+
+1. Clone this repository:
+
+   ```bash
+   git clone https://github.com/salmanalfarisi11/Upscaler_images.git
+   cd Upscaler_images
+   ```
+
+2. Create and activate a virtual environment:
+
+   ```bash
+    python -m venv .venv
+    source .venv/bin/activate   # Linux/macOS
+    .venv\Scripts\activate      # Windows
+   ```
+
+3. Install dependencies:
+
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+## 🚀 Running Locally
+
+Launch the app on your machine:
+   ```bash
+   python app.py
+   ```
+By default, it will start on http://127.0.0.1:7860/. Open that URL in your browser to access the interface.
+
+## 🎯 Usage
+
+1. **Upload Photo** via the left panel.  
+2. **Choose a Mode**:  
+   - Click **Standard Upscale (×4)** for a 4x resolution increase. 
+   - Click **Premium Upscale (×8)** for an 8x resolution increase.
+3. Preview your result on the right side. 
+4. Click **Download PNG** to save the upscaled image.
+
+
+## 🤝 Contributing
+Contributions, bug reports, and feature requests are welcome! Feel free to open an issue or submit a pull request.
+
+
+## 📄 License
+
+This project is licensed under the [MIT License](LICENSE).
+
+---
+
+## 🖋️ Author & Credits
+
+Developed by **[Salman Alfarisi](https://github.com/salmanalfarisi11)** © 2025  
+- GitHub: [salmanalfarisi11](https://github.com/salmanalfarisi11)  
+- LinkedIn: [salmanalfarisi11](https://linkedin.com/in/salmanalfarisi11)  
+- Instagram: [faris.salman111](https://instagram.com/faris.salman111)  
+
+Built with ❤️ and Gradio
+Feel free to ⭐ the repo and share feedback!
+
+## Acknowledgements
+This project uses the Real-ESRGAN model developed by Xintao Wang.
+The model is available under the BSD 3-Clause License.

app.py

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+import os
+import requests
+import numpy as np
+import onnxruntime as ort
+from PIL import Image
+import gradio as gr
+import tempfile
+
+# ——————————————————————————————————————————————————————————————
+# 1) Path ke ONNX model "×4"
+MODEL_DIR     = "model"
+MODEL_X4_PATH = os.path.join(MODEL_DIR, "Real-ESRGAN-x4plus.onnx")
+
+# Cek apakah model sudah ada, jika tidak, unduh dari GitHub
+if not os.path.isfile(MODEL_X4_PATH):
+    os.makedirs(MODEL_DIR, exist_ok=True)
+    model_url = "https://raw.githubusercontent.com/salmanalfarisi11/Upscaler_images/master/model/Real-ESRGAN-x4plus.onnx"  # Raw GitHub URL
+    response = requests.get(model_url)
+    with open(MODEL_X4_PATH, 'wb') as f:
+        f.write(response.content)
+    print(f"Model downloaded to {MODEL_X4_PATH}")
+
+# ——————————————————————————————————————————————————————————————
+# 2) Buat ONNXRuntime session hanya dengan CPU, 2 thread
+sess_opts = ort.SessionOptions()
+sess_opts.intra_op_num_threads = 2
+sess_opts.inter_op_num_threads = 2
+
+session_x4 = ort.InferenceSession(MODEL_X4_PATH, sess_options=sess_opts,
+                                  providers=["CPUExecutionProvider"])
+
+# Ambil metadata ukuran input tile untuk model ×4 (biasanya 128×128)
+input_meta_x4 = session_x4.get_inputs()[0]
+_, _, H_in_x4, W_in_x4 = tuple(input_meta_x4.shape)
+H_in_x4, W_in_x4 = int(H_in_x4), int(W_in_x4)
+
+# Cek skala (harusnya 4×)
+dummy = np.zeros((1, 3, H_in_x4, W_in_x4), dtype=np.float32)
+dummy_out = session_x4.run(None, {input_meta_x4.name: dummy})[0]
+_, _, H_out_x4, W_out_x4 = dummy_out.shape
+SCALE_X4 = H_out_x4 // H_in_x4
+if SCALE_X4 != 4:
+    raise RuntimeError(f"Model ×4 menghasilkan scale = {SCALE_X4}, bukan 4")
+
+# ——————————————————————————————————————————————————————————————
+# 3) Fungsi util untuk mem‐proses satu tile 128×128 → 512×512
+def run_tile_x4(tile_np: np.ndarray) -> np.ndarray:
+    """
+    Input: tile_np (128,128,3) float32 ∈ [0,1]
+    Output: (512,512,3) float32 ∈ [0,1]
+    """
+    patch_nchw = np.transpose(tile_np, (2, 0, 1))[None, ...]  # → (1,3,128,128)
+    out_nchw = session_x4.run(None, {input_meta_x4.name: patch_nchw})[0]  # (1,3,512,512)
+    out_nchw = np.squeeze(out_nchw, axis=0)            # (3,512,512)
+    out_hwc  = np.transpose(out_nchw, (1, 2, 0))        # (512,512,3)
+    return out_hwc  # float32 ∈ [0,1]
+
+# ——————————————————————————————————————————————————————————————
+# 4) Pipeline tile‐based untuk ×4 –– mem‐pad, potong, infer, reassemble, crop
+def tile_upscale_x4(input_img: Image.Image):
+    """
+    1. PIL→float32 np ∈ [0,1]
+    2. Pad agar (H,W) kelipatan H_in_x4 (128)
+    3. Bagi menjadi tile (H_in_x4 × W_in_x4)
+    4. run_tile_x4 per tile, simpan ke out_arr
+    5. Crop ke (orig_h*4, orig_w*4)
+    6. Convert ke uint8 PIL, save PNG, return (PIL, filepath)
+    """
+    # 4.1. Convert PIL→float32 [0,1]
+    img_rgb = input_img.convert("RGB")
+    arr = np.array(img_rgb).astype(np.float32) / 255.0  # (h_orig, w_orig, 3)
+    h_orig, w_orig, _ = arr.shape
+
+    # 4.2. Hitung jumlah tile dan padding
+    tiles_h = math.ceil(h_orig / H_in_x4)
+    tiles_w = math.ceil(w_orig / W_in_x4)
+    pad_h   = tiles_h * H_in_x4 - h_orig
+    pad_w   = tiles_w * W_in_x4 - w_orig
+
+    # Reflect pad di kanan + bawah
+    arr_padded = np.pad(
+        arr,
+        ((0, pad_h), (0, pad_w), (0, 0)),
+        mode="reflect"
+    )  # → (tiles_h * 128, tiles_w * 128, 3)
+
+    # 4.3. Buat array output berukuran (tiles_h*512, tiles_w*512, 3)
+    out_h = tiles_h * H_in_x4 * SCALE_X4
+    out_w = tiles_w * W_in_x4 * SCALE_X4
+    out_arr = np.zeros((out_h, out_w, 3), dtype=np.float32)
+
+    # 4.4. Loop semua tile
+    for i in range(tiles_h):
+        for j in range(tiles_w):
+            y0   = i * H_in_x4
+            x0   = j * W_in_x4
+            tile = arr_padded[y0 : y0 + H_in_x4, x0 : x0 + W_in_x4, :]  # (128,128,3)
+
+            up_tile = run_tile_x4(tile)  # (512,512,3) float32
+
+            oy0 = i * H_in_x4 * SCALE_X4
+            ox0 = j * W_in_x4 * SCALE_X4
+            out_arr[oy0 : oy0 + H_in_x4 * SCALE_X4,
+                    ox0 : ox0 + W_in_x4 * SCALE_X4, :] = up_tile
+
+    # 4.5. Crop → (h_orig*4, w_orig*4)
+    final_arr = out_arr[0 : h_orig * SCALE_X4, 0 : w_orig * SCALE_X4, :]
+    final_arr = np.clip(final_arr, 0.0, 1.0)
+    final_uint8 = (final_arr * 255.0).round().astype(np.uint8)
+    final_pil   = Image.fromarray(final_uint8)  # (h_orig*4, w_orig*4)
+
+    # 4.6. Simpan ke file PNG unik
+    tmp = tempfile.NamedTemporaryFile(delete=False, suffix=".png")
+    final_pil.save(tmp.name, format="PNG")
+    tmp.close()
+    return final_pil, tmp.name
+
+# ——————————————————————————————————————————————————————————————
+# 5) Fungsi Standard (×4) dan Premium (×8) untuk Gradio
+def standard_upscale(input_img: Image.Image):
+    # Hasil ×4 tile→reassemble 
+    return tile_upscale_x4(input_img)
+
+def premium_upscale(input_img: Image.Image):
+    """
+    - Jalankan pipeline ×4 untuk dapat final_4x (PIL)
+    - Lalu bicubic‐resize final_4x → 8× resolusi (orig_w*8, orig_h*8)
+    - Simpan PNG baru dan return (PIL_8x, filepath)
+    """
+    # 5.1. Pertama dapatkan output ×4
+    final_4x, path_4x = tile_upscale_x4(input_img)  # final_4x size = (h_orig*4, w_orig*4)
+
+    # 5.2. Ukuran asli
+    w_orig, h_orig = input_img.size
+
+    # 5.3. Resize bicubic (LANCZOS) dari 4× → 8×
+    target_size = (w_orig * 8, h_orig * 8)
+    final_8x = final_4x.resize(target_size, resample=Image.LANCZOS)
+
+    # 5.4. Simpan PNG unik
+    tmp = tempfile.NamedTemporaryFile(delete=False, suffix=".png")
+    final_8x.save(tmp.name, format="PNG")
+    tmp.close()
+
+    return final_8x, tmp.name
+
+# ——————————————————————————————————————————————————————————————
+# 6) CSS Kustom agar tombol Premium bergenre “emas”
+css = """
+#premium-btn {
+    background-color: gold !important;
+    color: black !important;
+}
+"""
+
+# ——————————————————————————————————————————————————————————————
+# 7) Bangun Gradio Blocks – 2 tombol berdampingan
+with gr.Blocks(css=css, title="Real-ESRGAN Dual-Mode Upscaler") as demo:
+    gr.Markdown(
+        """
+        # Real-ESRGAN Dual-Mode Upscaler  
+        **Standard Upscale** (×4) atau **Premium Upscale 🚀** (×8).  
+        Silakan upload gambar apa saja, kemudian klik tombol yang diinginkan.
+        """
+    )
+
+    # Baris untuk upload gambar
+    with gr.Row():
+        inp_image = gr.Image(type="pil", label="Upload Source Image")
+
+    # Baris untuk dua tombol
+    with gr.Row():
+        btn_std  = gr.Button("Standard Upscale (×4)", variant="primary", elem_id="std-btn")
+        btn_prem = gr.Button("Premium Upscale 🚀 (×8)", elem_id="premium-btn")
+
+    # Dua output: preview image & link “Download PNG”
+    out_preview  = gr.Image(type="pil", label="Upscaled Preview")
+    out_download = gr.DownloadButton("⬇️ Download PNG", visible=True)
+
+    # Hubungkan tombol ke fungsi:
+    btn_std.click(fn=standard_upscale, inputs=inp_image, outputs=[out_preview, out_download])
+    btn_prem.click(fn=premium_upscale, inputs=inp_image, outputs=[out_preview, out_download])
+
+demo.launch(server_name="0.0.0.0", server_port=7860)

requirements.txt

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+onnxruntime             # ONNX inference engine (CPU)
+numpy                   # Array manipulation
+Pillow                  # Image I/O
+gradio>=3.0             # Web UI