{ "cells": [ { "cell_type": "code", "execution_count": 52, "id": "9a6cbb9c-2521-4f01-8c83-d653ade653df", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "from pandas import DataFrame, Series # for convenience\n", "from skimage import morphology, util, filters\n", "from skimage.transform import warp_polar\n", "\n", "import pims\n", "import trackpy as tp\n", "\n", "import matplotlib as mpl\n", "import matplotlib.pyplot as plt\n", "\n", "# Optionally, tweak styles.\n", "mpl.rc('figure', figsize=(10, 5))\n", "mpl.rc('image', cmap='gray')" ] }, { "cell_type": "markdown", "id": "3dac9f80-5932-43a3-a588-6eea8c202d61", "metadata": {}, "source": [ "## Function for calculating particle centroid from a brightfield ring. " ] }, { "cell_type": "markdown", "id": "a05c8afc-385b-4ff9-a232-82512f43f02a", "metadata": {}, "source": [ "Only need to load this once after starting or restarting the kernel. You can also make a separate python functions file and import that above" ] }, { "cell_type": "code", "execution_count": 53, "id": "9efa81b1-2150-460c-aaa7-759192258c29", "metadata": {}, "outputs": [], "source": [ "from scipy.optimize import least_squares\n", "from skimage.transform import warp_polar\n", "def calc_centroid_brightfield(img,c0,r0,rbound,mask_r):\n", " \"\"\"\n", " Calculates centroid of a particle by fitting a circle to the darkest ring around the particle. Note in the raw image, the brightest ring is usually what \n", " is fit, so the image is passed inverted. \n", " From the initial guess of the centroid c0, the pixels < rbound around c0 are transformed to polar coordinates using skimage.transform.warp_polar\n", " Then, for each degree (warp_polar produces 360 rows/degrees), the boundary of the ring is estimated as the darkest point along that radial coordinate\n", " See SI Figure S2 of DOI:10.1039/C8SM01661E for the high-level picture of how this algorithm works\n", " REQUIRES: img - frame/image\n", " c0 - list of tuples of initial guess of particle centroids [(cx00,cy00),(cx01,cy01),...,(cx0N,cy0N)] for N particles\n", " r0 - initial guess of the radius of the darkest ring around the particle, units of pixels\n", " rbound - maximum radius around c0 to search for the dark ring, units of pixels\n", " RETURNS: list of particle centroid coordinates and radius, [cx,cy,r]\n", " \"\"\"\n", "\n", " def fit_fxn(vars,xdata,ydata):\n", " cx = vars[0]\n", " cy = vars[1]\n", " r = vars[2]\n", " #calculate residuals of radial positions from true radius\n", " radii = np.sqrt((xdata - cx)**2 + (ydata - cy)**2) - r\n", " return radii\n", " # find the particle boundary radially by converting to polar coordinates. Manually select initial guess interactively, then use guesses from previous frames\n", " # choose radius that is larger than the particle size. The radius bounds the region where the particle intensity is compared\n", " cx0 = c0[j][0]\n", " cy0 = c0[j][1]\n", "\n", " warped = warp_polar(img,center=(cy0,cx0),radius = rbound) #warping ix (y,x)\n", " theta = np.linspace(0,359,360)\n", "\n", " #CONSTRUCT PARTICLE RING. \n", " #this part of the code is something you could change in the future... e.g. could have multiple characteristic points per angle \n", " #estimate dark ring by the minimum brightness (darkest point for any given radial position)\n", " #mask points near the centroid by making them bright...in some images the center of the particle is brightest which throws off calculation\n", " if mask_r != 0 :\n", " warped[:,0:mask_r] = 255\n", " dark_ring = np.argmin(warped,axis=1)\n", " #estimate bright ring by the maximum brightness (lightest/whitest point for any given radial position)\n", " #bright_ring = np.argmax(warped,axis=1)\n", " \n", " #Convert these points back into x,y data \n", " xdata = dark_ring*np.cos(theta*np.pi/180)+cx0\n", " ydata = dark_ring*np.sin(theta*np.pi/180)+cy0\n", "\n", " #now that you have an estimate of the particle outline in cartesian, use least squares to determine the origin and radius. We care mostly about the origin\n", " lsq_result = least_squares(fit_fxn,[cx0,cy0,r0],args=([xdata,ydata]),loss='soft_l1')\n", " cx = lsq_result.x[0]\n", " cy = lsq_result.x[1]\n", " r = lsq_result.x[2]\n", "\n", " return [cx,cy,r]" ] }, { "cell_type": "markdown", "id": "51117400-3a8a-459d-b359-c8e98845ad50", "metadata": {}, "source": [ "## Load in video folder and setup some basic preprocessing " ] }, { "cell_type": "code", "execution_count": 54, "id": "36a9f5f6-f67f-484e-ae57-d05a7dc6ff98", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found 4 speed folders: ['0.1', '0.15', '0.2', '0.25']\n", " [0.1] 154 frames, shape: (1464, 1936)\n", " [0.15] 135 frames, shape: (1464, 1936)\n", " [0.2] 133 frames, shape: (1464, 1936)\n", " [0.25] 140 frames, shape: (1464, 1936)\n", "\n", "Done. Access a speed with: all_frames['0.25']\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/opt/anaconda3/lib/python3.12/site-packages/pims/image_sequence.py:85: FutureWarning: The plugin infrastructure in `skimage.io` and the parameter `plugin` are deprecated since version 0.25 and will be removed in 0.27 (or later). To avoid this warning, please do not use the parameter `plugin`. Instead, use `imageio` or other I/O packages directly. See also `imread`.\n", " return imread(filename, **kwargs)\n", "/opt/anaconda3/lib/python3.12/site-packages/pims/image_sequence.py:85: FutureWarning: The plugin infrastructure in `skimage.io` and the parameter `plugin` are deprecated since version 0.25 and will be removed in 0.27 (or later). To avoid this warning, please do not use the parameter `plugin`. Instead, use `imageio` or other I/O packages directly. See also `imread`.\n", " return imread(filename, **kwargs)\n", "/opt/anaconda3/lib/python3.12/site-packages/pims/image_sequence.py:85: FutureWarning: The plugin infrastructure in `skimage.io` and the parameter `plugin` are deprecated since version 0.25 and will be removed in 0.27 (or later). To avoid this warning, please do not use the parameter `plugin`. Instead, use `imageio` or other I/O packages directly. See also `imread`.\n", " return imread(filename, **kwargs)\n", "/opt/anaconda3/lib/python3.12/site-packages/pims/image_sequence.py:85: FutureWarning: The plugin infrastructure in `skimage.io` and the parameter `plugin` are deprecated since version 0.25 and will be removed in 0.27 (or later). To avoid this warning, please do not use the parameter `plugin`. Instead, use `imageio` or other I/O packages directly. See also `imread`.\n", " return imread(filename, **kwargs)\n" ] } ], "source": [ "import os\n", "\n", "# =============================================================================\n", "# SETTINGS\n", "# =============================================================================\n", "MAIN_FOLDER = r\"/Users/mpitell/Downloads/Drag tracking test\"\n", "TIFF_PATTERN = \"*.tiff\" # glob pattern for images inside each subfolder\n", "crop_dimensions = {'x_min': 800, 'x_max': 1100, 'y_min': 300, 'y_max': 1200}\n", "# =============================================================================\n", "\n", "@pims.pipeline\n", "def to_gray(image):\n", " if image.ndim == 3:\n", " return image[..., 1]\n", " return image\n", "\n", "@pims.pipeline\n", "def crop(img, crop_dimensions):\n", " return img[crop_dimensions['y_min']:crop_dimensions['y_max'],\n", " crop_dimensions['x_min']:crop_dimensions['x_max']]\n", "\n", "@pims.pipeline\n", "def invert(img):\n", " return 255 - img\n", "\n", "# --- Discover subfolders (each = one stage speed) ---\n", "subfolders = sorted([\n", " d for d in os.listdir(MAIN_FOLDER)\n", " if os.path.isdir(os.path.join(MAIN_FOLDER, d))\n", "])\n", "print(f\"Found {len(subfolders)} speed folders: {subfolders}\")\n", "\n", "# --- Load and preprocess all folders ---\n", "# all_frames[speed] = preprocessed (gray + crop) pims pipeline\n", "# all_frames_inv[speed] = inverted version (used during tracking)\n", "all_frames = {}\n", "all_frames_inv = {}\n", "\n", "for speed in subfolders:\n", " path = os.path.join(MAIN_FOLDER, speed, TIFF_PATTERN)\n", " raw = pims.open(path)\n", " gray = to_gray(raw)\n", " cropped = crop(gray, crop_dimensions)\n", " all_frames[speed] = cropped\n", " all_frames_inv[speed] = invert(cropped)\n", " print(f\" [{speed}] {len(raw)} frames, shape: {raw.frame_shape}\")\n", "\n", "print(\"\\nDone. Access a speed with: all_frames['0.25']\")" ] }, { "cell_type": "markdown", "id": "d705e72d-863d-471f-92df-987bb634eef9", "metadata": {}, "source": [ "## Setup for particle tracking" ] }, { "cell_type": "code", "execution_count": 55, "id": "6c850cd3-d1d4-4734-9454-58906cb14878", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Frame ranges per speed:\n", " [0.1] frames 0 – 153 (154 total)\n", " [0.15] frames 0 – 134 (135 total)\n", " [0.2] frames 0 – 132 (133 total)\n", " [0.25] frames 0 – 139 (140 total)\n" ] } ], "source": [ "num_particles = 3 # number of particles to track\n", "particle_r_bound = 50 # bounding radius around particle when determining centroid\n", "mask_r = 10 # masks bright region near particle center\n", "r0 = 35 # initial guess of bright ring radius\n", "\n", "# Start/end frames auto-detected per speed from the loaded image sequences\n", "frame_ranges = {\n", " speed: (0, len(all_frames[speed]) - 1)\n", " for speed in all_frames\n", "}\n", "\n", "# ploc_dict[speed] = 3D array (frames × particles × [cx, cy, r])\n", "ploc_dict = {\n", " speed: np.zeros((end - start + 1, num_particles, 3))\n", " for speed, (start, end) in frame_ranges.items()\n", "}\n", "\n", "print(\"Frame ranges per speed:\")\n", "for speed, (start, end) in frame_ranges.items():\n", " print(f\" [{speed}] frames {start} – {end} ({end - start + 1} total)\")" ] }, { "cell_type": "markdown", "id": "e8b3789e-84be-44b8-8e0d-02cd49012138", "metadata": {}, "source": [ "### manually hover over interactive plot to specify initial guesses of the particle centroids" ] }, { "cell_type": "code", "execution_count": 62, "id": "abbd2f16-1502-490d-b075-b3246381017e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Speeds: ['0.1', '0.15', '0.2', '0.25']\n", "Click 3 center(s) per image. Each speed opens its own figure.\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/opt/anaconda3/lib/python3.12/site-packages/pims/image_sequence.py:85: FutureWarning: The plugin infrastructure in `skimage.io` and the parameter `plugin` are deprecated since version 0.25 and will be removed in 0.27 (or later). To avoid this warning, please do not use the parameter `plugin`. Instead, use `imageio` or other I/O packages directly. See also `imread`.\n", " return imread(filename, **kwargs)\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "9aaecbee6c804337afea662ccac1c944", "version_major": 2, "version_minor": 0 }, "image/png": 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", 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