Upload 7 files

Dockerfile

@@ -0,0 +1,9 @@
+FROM python:3.10-slim
+
+RUN pip install --upgrade pip
+RUN pip install mercury==2.4.3
+
+COPY . /code
+WORKDIR /code
+
+CMD ["mercury", "run", "app.py"]

README.md

@@ -1,14 +1,14 @@
 ---
-title: Convert2Color Image
-emoji: 👁
-colorFrom: yellow
+title: Magic_Image_BlackWhite_To_Color
+emoji: 🌍
+colorFrom: blue
 colorTo: blue
 sdk: gradio
-sdk_version: 5.42.0
+sdk_version: 5.38.0
 app_file: app.py
 pinned: false
 license: cc
-short_description: Convert2Color_Image
+short_description: convert black and white to colored pictures
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,150 @@
+import os
+import cv2
+import numpy as np
+from flask import Flask, request, render_template, url_for
+from werkzeug.utils import secure_filename
+
+app = Flask(__name__, static_folder='static')
+
+# --- Directory Setup ---
+BASE_DIR = os.path.abspath(os.path.dirname(__file__))
+STATIC_FOLDER = os.path.join(BASE_DIR, 'static')
+UPLOAD_FOLDER = os.path.join(STATIC_FOLDER, 'uploads')
+OUTPUT_FOLDER = os.path.join(STATIC_FOLDER, 'outputs')
+MODEL_FOLDER = os.path.join(BASE_DIR, 'model')
+
+os.makedirs(STATIC_FOLDER, exist_ok=True)
+os.makedirs(UPLOAD_FOLDER, exist_ok=True)
+os.makedirs(OUTPUT_FOLDER, exist_ok=True)
+
+# --- Model paths ---
+protoPath = os.path.join(MODEL_FOLDER, 'colorization_deploy_v2.prototxt')
+modelPath = os.path.join(MODEL_FOLDER, 'colorization_release_v2.caffemodel')
+hullPath = os.path.join(MODEL_FOLDER, 'pts_in_hull.npy')
+
+assert os.path.exists(protoPath), f"Missing proto file: {protoPath}"
+assert os.path.exists(modelPath), f"Missing model file: {modelPath}"
+assert os.path.exists(hullPath), f"Missing hull file: {hullPath}"
+
+COLORIZATION_MODEL_AVAILABLE = False
+try:
+    print("Loading colorization model...")
+    net = cv2.dnn.readNetFromCaffe(protoPath, modelPath)
+    pts_in_hull = np.load(hullPath)
+
+    if pts_in_hull.shape != (313, 2):
+        raise ValueError(f"pts_in_hull shape invalid: {pts_in_hull.shape}")
+
+    pts = pts_in_hull.transpose().reshape(2, 313, 1, 1).astype(np.float32)
+
+    net.getLayer(net.getLayerId('class8_ab')).blobs = [pts]
+    net.getLayer(net.getLayerId('conv8_313_rh')).blobs = [np.full([1, 313], 2.606, dtype=np.float32)]
+
+    COLORIZATION_MODEL_AVAILABLE = True
+    print("Colorization model loaded successfully.")
+except Exception as e:
+    print(f"Failed to load colorization model: {e}")
+
+MAX_DIMENSION = 2048
+
+def resize_img(img):
+    h, w = img.shape[:2]
+    if max(h, w) > MAX_DIMENSION:
+        scale = MAX_DIMENSION / max(h, w)
+        return cv2.resize(img, (int(w * scale), int(h * scale)))
+    return img
+
+def adjust_brightness_contrast(img, brightness=0, contrast=20):
+    alpha = 1 + contrast / 100.0
+    return cv2.convertScaleAbs(img, alpha=alpha, beta=brightness)
+
+def colorize_image_local(input_path, output_path):
+    print(f"Reading image for colorization: {input_path}")
+    img = cv2.imread(input_path)
+    if img is None:
+        print("ERROR: Could not read input image (file may be corrupt or unreadable by OpenCV).")
+        return False
+    else:
+        print(f"Image loaded successfully, shape: {img.shape}")
+
+    if not COLORIZATION_MODEL_AVAILABLE:
+        print("Colorization model not available.")
+        return False
+
+    img = resize_img(img)
+    h, w = img.shape[:2]
+
+    img_rgb = img.astype("float32") / 255.0
+    lab = cv2.cvtColor(img_rgb, cv2.COLOR_BGR2LAB)
+    L = lab[:, :, 0]
+
+    L_resized = cv2.resize(L, (224, 224))
+    L_resized -= 50  # mean-centering
+
+    try:
+        net.setInput(cv2.dnn.blobFromImage(L_resized))
+        ab = net.forward()[0].transpose(1, 2, 0)
+    except Exception as e:
+        print(f"ERROR during DNN forward pass: {e}")
+        return False
+
+    ab = cv2.resize(ab, (w, h))
+    out_lab = np.concatenate((L[:, :, np.newaxis], ab), axis=2)
+    out_bgr = cv2.cvtColor(out_lab, cv2.COLOR_Lab2BGR)
+    out_bgr = np.clip(out_bgr * 255, 0, 255).astype("uint8")
+    out_bgr = adjust_brightness_contrast(out_bgr, brightness=-10, contrast=15)
+    cv2.imwrite(output_path, out_bgr)
+    print(f"Colorized image saved to {output_path}")
+    return True
+
+@app.route('/', methods=['GET', 'POST'])
+def index():
+
+    print(f"protoPath: {protoPath}, exists? {os.path.exists(protoPath)}")
+    print(f"modelPath: {modelPath}, exists? {os.path.exists(modelPath)}")
+    print(f"hullPath: {hullPath}, exists? {os.path.exists(hullPath)}")
+    print(f"UPLOAD_FOLDER: {UPLOAD_FOLDER}, exists? {os.path.exists(UPLOAD_FOLDER)}")
+    print(f"OUTPUT_FOLDER: {OUTPUT_FOLDER}, exists? {os.path.exists(OUTPUT_FOLDER)}")
+    print(f"COLORIZATION_MODEL_AVAILABLE: {COLORIZATION_MODEL_AVAILABLE}")
+    print(f"cv2 version: {cv2.__version__}")
+
+    original_url = enhanced_url = None
+    if request.method == 'POST':
+        file = request.files.get('image')
+        if file and file.filename:
+            filename = secure_filename(file.filename)
+            orig_path = os.path.join(UPLOAD_FOLDER, filename)
+            print(f"Saving file to {orig_path}")
+            try:
+                file.save(orig_path)
+                print(f"File saved successfully.")
+            except Exception as e:
+                print(f"ERROR: Failed to save file: {e}")
+                return "File save failed", 400
+
+            if os.path.exists(orig_path):
+                print(f"Saved file size: {os.path.getsize(orig_path)} bytes")
+            else:
+                print("ERROR: File does not exist after saving!")
+                return "File save failed", 400
+
+            output_name = f"output_{filename}"
+            output_path = os.path.join(OUTPUT_FOLDER, output_name)
+
+
+            if not colorize_image_local(orig_path, output_path):
+                print("Colorization failed inside colorize_image_local")
+                return "Colorization failed", 400
+
+            original_url = url_for('static', filename=f'uploads/{filename}')
+            enhanced_url = url_for('static', filename=f'outputs/{output_name}')
+        else:
+            print("No file uploaded or empty filename.")
+            return "No file uploaded", 400
+
+    return render_template('index.html', original_url=original_url, enhanced_url=enhanced_url)
+
+
+if __name__ == '__main__':
+    port = int(os.environ.get("PORT", 7860))
+    app.run(host='0.0.0.0', port=port, debug=False)

procfile

@@ -0,0 +1 @@
+gunicorn app:app --bind 0.0.0.0:$PORT

requirements.txt

@@ -0,0 +1,6 @@
+Flask==3.0.3
+flask-cors==4.0.1
+Werkzeug==3.0.3
+opencv-python==4.8.0.76
+opencv-python-headless==4.8.0.76
+numpy==1.26.4

templates/index.html

@@ -0,0 +1,199 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+<meta charset="UTF-8" />
+<meta name="viewport" content="width=device-width, initial-scale=1" />
+<title>Image Restoration & Colorization</title>
+<style>
+  @import url('https://fonts.googleapis.com/css2?family=Montserrat:wght@400;700&display=swap');
+
+  * {
+    box-sizing: border-box;
+  }
+
+  body {
+    font-family: 'Montserrat', sans-serif;
+    background: radial-gradient(circle at top left, #667eea, #764ba2, #6b46c1);
+    margin: 0;
+    padding: 40px 20px;
+    color: #fff;
+    min-height: 100vh;
+    display: flex;
+    flex-direction: column;
+    align-items: center;
+    background-attachment: fixed;
+  }
+
+  h1 {
+    font-weight: 700;
+    font-size: 3rem;
+    margin-bottom: 0.5em;
+    text-shadow: 0 3px 10px rgba(0,0,0,0.4);
+    text-align: center;
+    animation: fadeIn 1s ease-in-out;
+  }
+
+  form {
+    background: rgba(255, 255, 255, 0.15);
+    backdrop-filter: blur(10px);
+    border: 1px solid rgba(255,255,255,0.2);
+    border-radius: 16px;
+    padding: 35px;
+    max-width: 500px;
+    width: 100%;
+    box-shadow: 0 16px 32px rgba(0,0,0,0.25);
+    animation: slideIn 1s ease-out;
+  }
+
+  label {
+    display: block;
+    font-weight: 600;
+    margin-bottom: 10px;
+    margin-top: 20px;
+    font-size: 1.2rem;
+  }
+
+  input[type="file"] {
+    border: 2px dashed rgba(255,255,255,0.7);
+    background: rgba(255,255,255,0.1);
+    padding: 20px 14px;
+    border-radius: 12px;
+    width: 100%;
+    color: #f0f0f0;
+    font-weight: 500;
+    cursor: pointer;
+    transition: all 0.3s ease;
+  }
+
+  input[type="file"]:hover {
+    border-color: #fff;
+    background: rgba(255,255,255,0.15);
+  }
+
+  button {
+    margin-top: 30px;
+    width: 100%;
+    padding: 16px 0;
+    font-size: 1.3rem;
+    font-weight: 700;
+    color: #fff;
+    border: none;
+    border-radius: 30px;
+    background: linear-gradient(90deg, #ff758c, #ff7eb3);
+    cursor: pointer;
+    box-shadow: 0 8px 16px rgba(255,120,150,0.6);
+    transition: transform 0.2s ease, box-shadow 0.2s ease;
+  }
+
+  button:hover {
+    transform: translateY(-3px);
+    box-shadow: 0 12px 24px rgba(255,150,180,0.8);
+  }
+
+  .preview {
+    margin-top: 50px;
+    display: flex;
+    justify-content: center;
+    gap: 30px;
+    flex-wrap: wrap;
+    max-width: 1000px;
+    width: 100%;
+  }
+
+  .preview > div {
+    flex: 1 1 45%;
+    text-align: center;
+    animation: fadeInUp 1s ease forwards;
+  }
+
+  .preview img {
+    max-width: 100%;
+    max-height: 400px;
+    border-radius: 16px;
+    box-shadow: 0 12px 28px rgba(0,0,0,0.4);
+    border: 4px solid rgba(255, 255, 255, 0.25);
+    object-fit: contain;
+    background: #111;
+  }
+
+  .preview h3 {
+    margin-bottom: 14px;
+    font-weight: 700;
+    font-size: 1.4rem;
+    text-shadow: 0 2px 6px rgba(0,0,0,0.4);
+  }
+
+  .download-link {
+    display: inline-block;
+    margin-top: 12px;
+    font-size: 1.2rem;
+    color: #fff;
+    text-decoration: none;
+    background: rgba(255,255,255,0.25);
+    padding: 10px 16px;
+    border-radius: 10px;
+    transition: background 0.3s ease, transform 0.2s ease;
+  }
+
+  .download-link:hover {
+    background: rgba(255,255,255,0.4);
+    transform: scale(1.05);
+  }
+
+  @media (max-width: 640px) {
+    form {
+      max-width: 100%;
+      padding: 28px 22px;
+    }
+    .preview > div {
+      flex-basis: 100%;
+    }
+  }
+
+  @keyframes fadeIn {
+    from { opacity: 0; transform: translateY(-20px); }
+    to { opacity: 1; transform: translateY(0); }
+  }
+
+  @keyframes slideIn {
+    from { opacity: 0; transform: translateY(40px); }
+    to { opacity: 1; transform: translateY(0); }
+  }
+
+  @keyframes fadeInUp {
+    from { opacity: 0; transform: translateY(20px); }
+    to { opacity: 1; transform: translateY(0); }
+  }
+
+</style>
+</head>
+<body>
+
+  <h1>✨ Image Restoration &amp; Colorization</h1>
+
+  <form method="POST" enctype="multipart/form-data" novalidate>
+    <label for="image">Upload Damaged Image</label>
+    <input id="image" type="file" name="image" accept="image/*" required>
+
+    <button type="submit">✨ Enhance &amp; Colorize</button>
+  </form>
+
+  {% if original_url and enhanced_url %}
+    <section class="preview" aria-label="Image preview section">
+      <div>
+        <h3>Original Image</h3>
+        <img src="{{ original_url }}" alt="Original uploaded image preview" loading="lazy" />
+      </div>
+      <div>
+        <h3>Enhanced Image</h3>
+        <img src="{{ enhanced_url }}" alt="Enhanced processed image preview" loading="lazy" />
+        <br />
+        <a class="download-link" href="{{ enhanced_url }}" download>
+          ⬇️ Download Enhanced Image
+        </a>
+      </div>
+    </section>
+  {% endif %}
+
+</body>
+</html>