Add watermark removal project (not finished)

Author: RoundofThree

.gitignore

@@ -127,3 +127,9 @@ dmypy.json
 
 # Pyre type checker
 .pyre/
+
+# Mac
+.DS_Store 
+
+# vscode 
+.vscode 

watermark_removal/images/removed1.png

@@ -0,0 +1,220 @@
+{
+ "metadata": {
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.2"
+ },
+ "orig_nbformat": 2,
+ "kernelspec": {
+ "name": "python392jvsc74a57bd0eafa71b4a5f824d3055ca9707dde86e6ce800dc54c56e20c6da9d851446cd008",
+ "display_name": "Python 3.9.2 64-bit ('venv')"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2,
+ "cells": [
+ {
+ "source": [
+ "## Detect watermark \n",
+ "\n",
+ "*Note*: This is only for white semitransparent watermark. \n",
+ "\n",
+ "Find the pixels that contain a transparency "
+ ],
+ "cell_type": "markdown",
+ "metadata": {}
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import cv2 as cv\n",
+ "import numpy as np "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "image = \"./images/test1.jpg\"\n",
+ "# image = \"./images/test2-nored.jpg\"\n",
+ "# image = \"./images/test3.jpg\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "watermarked = cv.imread(image)\n",
+ "# display\n",
+ "def display(name, img):\n",
+ " cv.startWindowThread()\n",
+ " cv.imshow(name, img/255)\n",
+ " cv.waitKey(0)\n",
+ " cv.destroyWindow(name)\n",
+ " cv.waitKey(1)\n",
+ "\n",
+ "display(\"Watermarked\", watermarked)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# obtain the alpha mask\n",
+ "\n",
+ "# rectangle to identify watermark\n",
+ "# test1 \n",
+ "x, y, w, h = 600, 1400, 250, 35 \n",
+ "# test2 \n",
+ "# x, y, w, h = 580, 1480, 470, 70 \n",
+ "# test3 \n",
+ "# x, y, w, h = 600, 1400, 250, 35 \n",
+ "\n",
+ "selected = np.zeros_like(watermarked)\n",
+ "cv.rectangle(selected, (x,y), (x+w, y+h), (255,255,255), -1)\n",
+ "\n",
+ "# greyscale (for darker images such as test1)\n",
+ "watermark = cv.bitwise_and(watermarked, selected) \n",
+ "watermark = watermark.astype(float)\n",
+ "display(\"Selected\", watermark)\n",
+ "grey = watermark.max(axis=-1)\n",
+ "grey[grey>200] = 255 \n",
+ "grey[grey!=255] = 0 \n",
+ "display(\"Alpha mask\", grey)\n",
+ "\n",
+ "# for lighter images (test2 and test3)\n",
+ "# highlighted = cv.imread(\"./images/test2.jpg\")\n",
+ "# watermark = cv.bitwise_and(highlighted, selected) \n",
+ "# watermark = watermark.astype(float)\n",
+ "# display(\"Selected\", watermark)\n",
+ "# watermark[np.where((watermark == [0,0,255]).all(axis = 2))] = [255,255,255]\n",
+ "# watermark[np.where((watermark != [0,0,255]).all(axis = 2))] = [0,0,0]\n",
+ "# grey = watermark.max(axis=-1)\n",
+ "# grey[grey>0] = 255\n",
+ "# display(\"Mask\", grey)\n",
+ "\n",
+ "# HSV (alternative)\n",
+ "# hsv = cv.cvtColor(watermark, cv.COLOR_BGR2HSV)\n",
+ "# sensitivity = 50\n",
+ "# lower_white = np.array([0, 0, 255-sensitivity])\n",
+ "# upper_white = np.array([255, sensitivity, 255])\n",
+ "# hsv_mask = cv.inRange(hsv, lower_white, upper_white)\n",
+ "# display(\"Mask\", hsv_mask)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "name": "stdout",
+ "text": [
+ "Alpha is 0.9874781183456597\n"
+ ]
+ }
+ ],
+ "source": [
+ "W = grey\n",
+ "alpha_0 = 1.1* watermark[W!=0].mean()/255 # estimate alpha \n",
+ "alpha = np.zeros_like(W)\n",
+ "alpha[W==255] = alpha_0\n",
+ "print(\"Alpha is \", alpha_0)\n",
+ "\n",
+ "# for light images \n",
+ "# W = grey \n",
+ "# alpha = np.zeros_like(W)\n",
+ "# alpha[W>0] = 1 \n",
+ "\n",
+ "alpha = np.repeat(alpha, 3, axis=-1).reshape(*(alpha.shape),3)\n",
+ "W = np.repeat(W, 3, axis=-1).reshape(*(W.shape),3)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# NOT USED \n",
+ "def blur_mask(watermarked, alpha, W):\n",
+ " I = (watermarked.astype(float) - alpha * W)/(1-alpha)\n",
+ " I[I<0] = 0 \n",
+ " I[I>255] = 255 \n",
+ " I = I.astype(uint8)\n",
+ "\n",
+ " fI = I.copy()\n",
+ " fI[y:y+h, x:x+w, :] = cv.medianBlur(fI[y:y+h, x:x+w, :], 5) \n",
+ "\n",
+ " "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def process(watermarked, alpha, W, bg, output_name=\"removed.png\"):\n",
+ " aW = (alpha * W)\n",
+ " # a1 = (1 / (1-alpha))\n",
+ " med = bg \n",
+ " watermarked = watermarked.astype(float)\n",
+ " J = watermarked\n",
+ "\n",
+ " # display(\"Watermarked\", J)\n",
+ " # display(\"aW\", aW)\n",
+ " I = (J - aW) # * a1, but for test1, alpha is around 1\n",
+ " # display(\"I\", I)\n",
+ " I[I<0] = 0\n",
+ " I[I>255] = 255 \n",
+ " I = I.astype(np.uint8)\n",
+ "\n",
+ " display(\"Output\", I) \n",
+ "\n",
+ " # blur \n",
+ " fI = I.copy() \n",
+ " fI[y:y+h, x:x+w, :] = cv.medianBlur(fI[y:y+h, x:x+w, :], 7) \n",
+ " fI[fI<0] = 0\n",
+ " fI[fI>255] = 255 \n",
+ "\n",
+ " display(\"Output2\", fI)\n",
+ " cv.imwrite(output_name, fI)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "process(watermarked, alpha, W, W, \"./images/removed1.png\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ]
+}