feat: 增加相似度算法代码

Author: wangyinyuan

Diff for: .DS_Store

@@ -0,0 +1,14 @@
+const customParseFormat = require('dayjs/plugin/customParseFormat');
+const dayjs = require('dayjs');
+
+dayjs.extend(customParseFormat);
+
+function test() {
+  const dayFormat = 'D/M/YYYY';
+  const dateA = dayjs('3/4/2024', dayFormat);
+  const dateB = dayjs('12/9/2023', dayFormat);
+  console.log('dateA :', dateA.toDate());
+  console.log('dateB :',dateB.toDate());
+}
+
+test();

Diff for: express-backend/.DS_Store

@@ -0,0 +1,108 @@
+import glob
+import os
+import requests
+from flask import Flask, request, jsonify
+from PIL import Image
+from io import BytesIO
+
+EXTS = ('jpg', 'jpeg', 'JPG', 'JPEG', 'gif', 'GIF', 'png', 'PNG')
+
+app = Flask(__name__)
+
+def dhash(image, hash_size=8):
+    # Resize and convert image to grayscale
+    image = image.resize((hash_size + 1, hash_size), Image.Resampling.LANCZOS)
+
+    pixels = list(image.getdata())
+    # Compare adjacent pixels.
+    difference = []
+    for row in range(hash_size):
+        for col in range(hash_size):
+            pixel_left = pixels[row * (hash_size + 1) + col]
+            pixel_right = pixels[row * (hash_size + 1) + col + 1]
+            difference.append(pixel_left > pixel_right)
+
+    # Convert the binary array to a hexadecimal string.
+    decimal_value = 0
+    hex_string = []
+    for index, value in enumerate(difference):
+        if value:
+            decimal_value += 2 ** (index % 8)
+        if (index % 8) == 7:
+            hex_string.append(hex(decimal_value)[2:].rjust(2, '0'))
+            decimal_value = 0
+
+    return ''.join(hex_string)
+
+def dhash_rgb(image, hash_size=8):
+    # Ensure image is RGB
+    if image.mode != 'RGB':
+        image = image.convert('RGB')
+    # Split the image into R, G, B channels
+    r, g, b = image.split()
+    return dhash(r, hash_size), dhash(g, hash_size), dhash(b, hash_size)
+
+def hamming(h1, h2):
+    return sum(c1 != c2 for c1, c2 in zip(h1, h2))
+
+def hamming_to_similarity(hamming_distance, max_distance):
+    return 1 - (hamming_distance / max_distance)
+
+@app.route('/similarity', methods=['POST'])
+def calculate_similarity():
+    if 'file' not in request.files:
+        return jsonify({'error': 'No file part'}), 400
+
+    file = request.files['file']
+    if file.filename == '':
+        return jsonify({'error': 'No selected file'}), 400
+
+    url = request.form.get('url')
+    if not url:
+        return jsonify({'error': 'No URL provided'}), 400
+
+    try:
+        # Download the base image from the URL
+        response = requests.get(url)
+        response.raise_for_status()
+        base_image = Image.open(BytesIO(response.content))
+    except Exception as e:
+        return jsonify({'error': 'Failed to download base image', 'message': str(e)}), 400
+
+    try:
+        # Load the candidate image from the uploaded file
+        candidate_image = Image.open(file.stream)
+    except Exception as e:
+        return jsonify({'error': 'Failed to load candidate image', 'message': str(e)}), 400
+
+    # Calculate dHash for both images
+    base_hash_r, base_hash_g, base_hash_b = dhash_rgb(base_image)
+    hash_r, hash_g, hash_b = dhash_rgb(candidate_image)
+
+    # Calculate Hamming distances
+    ham_dist_r = hamming(base_hash_r, hash_r)
+    ham_dist_g = hamming(base_hash_g, hash_g)
+    ham_dist_b = hamming(base_hash_b, hash_b)
+
+    max_distance = 8 * 8  # Maximum hamming distance for each channel
+    similarity_r = hamming_to_similarity(ham_dist_r, max_distance)
+    similarity_g = hamming_to_similarity(ham_dist_g, max_distance)
+    similarity_b = hamming_to_similarity(ham_dist_b, max_distance)
+
+    # Average similarity over all channels
+    similarity = (similarity_r + similarity_g + similarity_b) / 3
+
+    return jsonify({
+        'similarity': similarity,
+        'details': {
+            'ham_dist_r': ham_dist_r,
+            'ham_dist_g': ham_dist_g,
+            'ham_dist_b': ham_dist_b,
+            'similarity_r': similarity_r,
+            'similarity_g': similarity_g,
+            'similarity_b': similarity_b
+        }
+    })
+
+if __name__ == '__main__':
+    app.run(debug=True)