{ "cells": [ { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "from PIL import Image\n", "import numpy as np\n", "\n", "import albumentations as A\n", "\n", "%config InlineBackend.figure_formats = ['svg']\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "image/svg+xml": "\n\n\n", "text/plain": [ "

" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "img = Image.open(\"/tmp/extract/photo.jpg\").convert(\"RGBA\")\n", "mask = Image.open(\"/tmp/extract/MASK.PNG\").convert(\"LA\")\n", "\n", "plt.figure(figsize=(18, 10))\n", "\n", "plt.subplot(1, 2, 1)\n", "plt.imshow(img)\n", "\n", "plt.subplot(1, 2, 2)\n", "plt.imshow(mask)\n", "\n", "ax = plt.gca()\n", "ax.set_facecolor('xkcd:salmon')\n", "\n", "plt.show()\n" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "image/svg+xml": "\n\n\n", "text/plain": [ "

" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "(434, 425)\n" ] } ], "source": [ "box = mask.getbbox()\n", "\n", "crop_img = img.crop(box)\n", "crop_mask = mask.crop(box)\n", "\n", "plt.figure(figsize=(18, 10))\n", "\n", "plt.subplot(2, 2, 1)\n", "plt.imshow(crop_img)\n", "\n", "plt.subplot(2, 2, 2)\n", "plt.imshow(crop_mask)\n", "\n", "ax = plt.gca()\n", "ax.set_facecolor('xkcd:salmon')\n", "\n", "empty = Image.fromarray(np.zeros(crop_img.size), \"RGBA\")\n", "empty.paste(crop_img, crop_mask)\n", "\n", "plt.subplot(2, 2, 3)\n", "plt.imshow(empty.resize((100, 100)))\n", "\n", "plt.subplot(2, 2, 4)\n", "plt.imshow(crop_mask.resize((100, 100)))\n", "\n", "ax = plt.gca()\n", "ax.set_facecolor('xkcd:salmon')\n", "\n", "plt.show()\n", "\n", "print(crop_img.size)" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [], "source": [ "from pathlib import Path\n", "\n", "spheres_to_extract_dir = \"/home/lilian/data_disk/lfainsin/test/\"\n", "\n", "spheres = list(Path(spheres_to_extract_dir).glob(\"**/*.jpg\"))\n", "\n", "parents = [path.parent for path in spheres]\n", "parents = set(parents)\n", "\n", "for parent in parents:\n", " mask_path = parent.joinpath(\"MASK.PNG\")\n", " mask = Image.open(mask_path).convert(\"LA\")\n", " box = mask.getbbox()\n", " crop_mask = mask.crop(box)\n", "\n", " filename = Path(\"/tmp/saves/\" + str(mask_path).strip(spheres_to_extract_dir))\n", " filename.parent.mkdir(parents=True, exist_ok=True)\n", " crop_mask.save(filename)\n", "\n", " spheres = list(parent.glob(\"*.jpg\"))\n", " for sphere in spheres:\n", " img = Image.open(sphere).convert(\"RGB\")\n", " crop_img = img.crop(box)\n", "\n", " filename = Path(\"/tmp/saves/\" + str(sphere).strip(spheres_to_extract_dir))\n", " filename.parent.mkdir(parents=True, exist_ok=True)\n", " crop_img.save(filename)\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3.8.0 ('.venv': poetry)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.0" }, "orig_nbformat": 4, "vscode": { "interpreter": { "hash": "dc80d2c03865715c8671359a6bf138f6c8ae4e26ae025f2543e0980b8db0ed7e" } } }, "nbformat": 4, "nbformat_minor": 2 }