{ "cells": [ { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "# Standard imports for python, images and metadata\n", "\n", "from PIL import Image\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from scipy import ndimage\n", "import os\n", "import json\n", "import piexif\n", "import logging" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "def plot(dir):\n", " # prepares a plot of the height against Laplacian sharpness and JPEG size for SD and HD images. Takes height from images beginning with a number\n", "\n", " x_SD = []\n", " x_HD = []\n", " image_list = []\n", " Lap_SD = []\n", " Lap_HD = []\n", " size_SD = []\n", " size_HD = []\n", "\n", " # Make a list of .jpeg images in the dir (which don't contain the word 'graph') and sort them. Relies on images having a naming convention linked to their heights\n", " # Otherwise, all other lists need to be zipped and reordered according to x_SD and x_HD.\n", "\n", " image_list = [os.path.join(dir, f) for f in os.listdir(dir) if 'graph' not in f and f[-5:] == '.jpeg']\n", " image_list.sort()\n", " \n", " # For each image, open it, and append to the relevant list the x position, file size and Laplacian sharpness\n", " for item in image_list:\n", " link = item\n", " picture = Image.open(link)\n", " data = np.asarray(picture)\n", " if 'SD.jpeg' in link:\n", " Lap_SD.append(sharpness_sum_lap2(data))\n", " size_SD.append(os.path.getsize(link)/1000000)\n", " x_SD.append(int(pull_usercomment_dict(link)['instrument']['state']['stage']['position']['z']))\n", " elif 'HD.jpeg' in link:\n", " size_HD.append(os.path.getsize(link)/1000000)\n", " Lap_HD.append(sharpness_sum_lap2(data))\n", " x_HD.append(int(pull_usercomment_dict(link)['instrument']['state']['stage']['position']['z']))\n", "\n", " return x_SD, x_HD, Lap_SD, Lap_HD, size_SD, size_HD\n", "\n", "\n", "def pull_usercomment_dict(filepath):\n", " \"\"\"\n", " Reads UserComment Exif data from a file, and returns the contained bytes as a dictionary.\n", " Args:\n", " filepath: Path to the Exif-containing file\n", " \"\"\"\n", " try:\n", " exif_dict = piexif.load(filepath)\n", " except piexif.InvalidImageDataError:\n", " logging.warning(\"Invalid data at {}. Skipping.\".format(filepath))\n", " return None\n", " if \"Exif\" in exif_dict and piexif.ExifIFD.UserComment in exif_dict[\"Exif\"]:\n", " try:\n", " return json.loads(exif_dict[\"Exif\"][piexif.ExifIFD.UserComment].decode())\n", " except json.decoder.JSONDecodeError:\n", " logging.error(\n", " f\"Capture {filepath} has old, corrupt, or missing OpenFlexure metadata. Unable to reload to server.\"\n", " )\n", " else:\n", " return None" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "def sharpness_sum_lap2(rgb_image):\n", " \"\"\"Return an image sharpness metric: sum(laplacian(image)**\")\"\"\"\n", " image_bw = np.mean(rgb_image, 2)\n", " image_lap = ndimage.filters.laplace(image_bw)\n", " return np.mean(np.abs(image_lap.astype(np.float) ** 2)) * 1000" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "# run this to analyse images already saved locally. dir should point to a folder containing the images to be analysed\n", "\n", "dir = r'\\11'\n", "x_SD, x_HD, Lap_SD, Lap_HD, size_SD, size_HD = plot(dir)\n", "\n", "# Positions converted from steps to physical relative position\n", "\n", "x_SD = [x/20 for x in x_SD]\n", "x_HD = [x/20 for x in x_HD]" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Plot the resulting heights and sharpnesses\n", "\n", "fig, ax1 = plt.subplots()\n", "\n", "ax1.plot(x_SD, [x / 1000 for x in Lap_SD], marker = '.',linewidth = 1, color = 'red', label = 'DR images')\n", "ax1.tick_params(axis='y')\n", "ax1.xaxis.set_tick_params(labelsize=12)\n", "ax1.set_ylabel('DR Lap. Sharpness (arb)', fontsize=16, color = 'red')\n", "ax1.set_xlabel('Relative objective position (µm)', fontsize=16)\n", "ax1.tick_params(axis='both', which='major', labelsize=14)\n", "\n", "\n", "ax2 = ax1.twinx()\n", "ax2.plot(x_HD, [x / 1000 for x in Lap_HD], marker = '.',linewidth = 1, color = 'blue', label = 'FR images')\n", "ax2.set_ylabel('FR Lap. Sharpness (arb)', fontsize=16, color = 'blue')\n", "ax2.tick_params(axis='y', color = 'blue')\n", "ax2.tick_params(axis='both', which='major', labelsize=14)\n", "ax2.text(0.04, 0.16, 'Laplacian', fontsize = 16, horizontalalignment='left', verticalalignment='top', transform=ax2.transAxes)\n", "\n", "# A manually judged focused range\n", "focus_1 = 1784/20\n", "focus_2 = 1884/20\n", "ax2.fill_between([focus_1,focus_2], min(Lap_HD)/1000, max(Lap_HD)/1000, facecolor='green', alpha=0.4, label = 'Focused range')\n", "\n", "lines, labels = ax1.get_legend_handles_labels()\n", "lines2, labels2 = ax2.get_legend_handles_labels()\n", "ax2.legend(lines + lines2, labels + labels2, fontsize = 12, loc = (0.265,0.7))\n", "plt.show()\n", "\n", "fig, ax1 = plt.subplots()\n", "\n", "ax1.plot(x_SD, [x * 1000 for x in size_SD], marker = '.', linewidth = 1, color = 'red', label = 'DR images')\n", "ax1.tick_params(axis='y')\n", "ax1.xaxis.set_tick_params(labelsize=12)\n", "ax1.set_ylabel('DR JPEG size (kB)', fontsize=16, color = 'red')\n", "ax1.set_xlabel('Relative objective position (µm)', fontsize=16)\n", "ax1.tick_params(axis='both', which='major', labelsize=14)\n", "\n", "\n", "ax2 = ax1.twinx()\n", "ax2.plot(x_HD, size_HD, color = 'blue', marker = '.', linewidth = 1, label = 'FR images')\n", "ax2.set_ylabel('FR JPEG size (MB)',fontsize=16, color = 'blue')\n", "ax2.tick_params(axis='y')\n", "ax2.tick_params(axis='both', which='major', labelsize=14)\n", "ax2.fill_between([focus_1,focus_2], min(size_HD), max(size_HD), facecolor='green', alpha=0.4, label = 'Focused range')\n", "ax2.text(0.04, 0.16, 'JPEG size', fontsize = 16, horizontalalignment='left', verticalalignment='top', transform=ax2.transAxes)\n", "\n", "lines, labels = ax1.get_legend_handles_labels()\n", "lines2, labels2 = ax2.get_legend_handles_labels()\n", "ax2.legend(lines + lines2, labels + labels2, fontsize = 12, loc = (0.265,0.7)) #, bbox_transform=ax2.transAxes)\n", "plt.show()" ] } ], "metadata": { "interpreter": { "hash": "aa28e4f14a7ff8b2d1fa149f2498635dcaf698094ea98853a01965ff2586af7e" }, "kernelspec": { "display_name": "Python 3.8.2 64-bit ('.venv': poetry)", "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": "3.8.2" }, "metadata": { "interpreter": { "hash": "dcd99e123aefb345c81b2d21fbce0c90f7dc858f2eb0d795f04cc6967c602773" } }, "orig_nbformat": 2 }, "nbformat": 4, "nbformat_minor": 2 }