Upload water_marking.py

water_marking.py

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+import cv2
+import numpy as np
+from pywt import dwt2, idwt2  # For DWT watermarking
+
+# ---------- CONFIG ----------
+victim_id_path = "new_cases/WhatsApp Image 2025-04-18 at 14.45.03.jpeg"       # Victim's ID face
+scammer_selfie_path = "new_cases/hardik_picture.jpg"    # Scammer's face image
+face_swapped_path = "new_cases/ChatGPT Image May 25, 2025, 10_52_19 AM.png"  # Output of deepfake tool (SimSwap)
+final_output_path = "new_cases/forged_with_watermark.jpg"
+
+GPT_Key = "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"
+
+def embed_watermark_dwt_color(host_image_path, watermark_image_path, alpha=0.3):
+    # Load and resize images
+    host = cv2.imread(host_image_path)
+    host = cv2.resize(host, (380, 507))
+    watermark = cv2.imread(watermark_image_path)
+    watermark = cv2.resize(watermark, (380, 507))
+
+    # Split into channels
+    host_channels = cv2.split(host)
+    wm_channels = cv2.split(watermark)
+
+    # Watermark each channel using DWT
+    watermarked_channels = []
+    for h_channel, wm_channel in zip(host_channels, wm_channels):
+        LL, (LH, HL, HH) = dwt2(h_channel, 'haar')
+        wLL, (wLH, wHL, wHH) = dwt2(wm_channel, 'haar')
+        wLH = cv2.resize(wLH, (LH.shape[1], LH.shape[0]))
+        LL_wm =  0.1 * (wHH) + 0.60 * LL + 0.40 * wLL
+        coeffs = (LL_wm, (wLH, wHL, wHH))
+        watermarked = idwt2(coeffs, 'haar')
+        watermarked_channels.append(np.clip(watermarked, 0, 255).astype(np.uint8))
+
+    # Merge channels back
+    watermarked_img = cv2.merge(watermarked_channels)
+    return watermarked_img
+
+# Run the watermark embedding
+watermarked_img = embed_watermark_dwt_color(face_swapped_path, victim_id_path)
+
+# Save the output
+cv2.imwrite(final_output_path, watermarked_img)
+final_output_path