diff --git "a/Networks/experiments_with_devolearn_node_maps.ipynb" "b/Networks/experiments_with_devolearn_node_maps.ipynb" new file mode 100644--- /dev/null +++ "b/Networks/experiments_with_devolearn_node_maps.ipynb" @@ -0,0 +1,961 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "8V_XhlJhAqLz" + }, + "source": [ + "## Explorations with DevoLearn\n", + "\n", + "The objectives of this notebook are:\n", + "\n", + "* Visualize the distances between the centroids of each cell in the C. elegans embryo during embryogenesis \n", + "\n", + "* Try and make a 3d model of the C. elegans emryo using images from n different planes of the same embryo. \n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "w5V0UII_wYyv" + }, + "outputs": [], + "source": [ + "!pip install devolearn" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "FDiViDBTwi1u" + }, + "outputs": [], + "source": [ + "import os\n", + "import matplotlib.pyplot as plt \n", + "import pandas as pd\n", + "import numpy as np\n", + "import cv2\n", + "from IPython.display import clear_output\n", + "from scipy.spatial import distance" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "gnHjuCgmBsYG" + }, + "source": [ + "In our case, we import the `embryo_segmentor` model, you can learn more about it [here](https://github.com/DevoLearn/devolearn#segmenting-the-c-elegans-embryo)\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "mb8bgNY4woSY" + }, + "outputs": [], + "source": [ + "from devolearn import embryo_segmentor" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "ELxrqvgiws1H" + }, + "outputs": [], + "source": [ + "model = embryo_segmentor()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "JZl0qSMpCMHk" + }, + "source": [ + "### Loading and extracting image data from google drive \n", + "\n", + "If you want a copy of the image data for yourself, feel free to get in touch with us on [slack workspace](https://openworm.slack.com/archives/CMVFU7Q4W)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "gk1yC3YDwwNi" + }, + "outputs": [], + "source": [ + "!cp /content/drive/\"My Drive\"/segmentation/3d_segmentation/training_data.zip /content/\n", + "!cp /content/drive/\"My Drive\"/segmentation/3d_segmentation/metadata.csv /content/" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "mH73nMZ1xCr0" + }, + "outputs": [], + "source": [ + "!unzip training_data.zip " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 194 + }, + "colab_type": "code", + "id": "dmoi-GW0xEnG", + "outputId": "f08eb381-c9cd-4b3a-e86c-ca74224c6e54" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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imagemask
8925training_data/images/real_94_55.jpgtraining_data/masks/mask_94_55_1.jpg
8926training_data/images/real_94_56.jpgtraining_data/masks/mask_94_56_0.jpg
8927training_data/images/real_94_56.jpgtraining_data/masks/mask_94_56_1.jpg
8928training_data/images/real_94_57.jpgtraining_data/masks/mask_94_57_0.jpg
8929training_data/images/real_94_57.jpgtraining_data/masks/mask_94_57_1.jpg
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" + ], + "text/plain": [ + " image mask\n", + "8925 training_data/images/real_94_55.jpg training_data/masks/mask_94_55_1.jpg\n", + "8926 training_data/images/real_94_56.jpg training_data/masks/mask_94_56_0.jpg\n", + "8927 training_data/images/real_94_56.jpg training_data/masks/mask_94_56_1.jpg\n", + "8928 training_data/images/real_94_57.jpg training_data/masks/mask_94_57_0.jpg\n", + "8929 training_data/images/real_94_57.jpg training_data/masks/mask_94_57_1.jpg" + ] + }, + "execution_count": 352, + "metadata": { + "tags": [] + }, + "output_type": "execute_result" + } + ], + "source": [ + "df = pd.read_csv(\"metadata.csv\")\n", + "df.tail()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "9vRV2ommC3VO" + }, + "source": [ + "## Selecting the images of a single embryo for experimentation\n", + "\n", + "We would first try to extract the centroids of a single embryo's cells while it undergoes embryogenesis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "OqmmWFWnxP9Z" + }, + "outputs": [], + "source": [ + "image_paths = df[df[\"image\"].str.contains(\"25.jpg\") == True][\"image\"].unique()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "btB_OWLgFQ8D" + }, + "source": [ + "Notice how `centroid_mode` is set to `True`\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "DszYuaJVxnV3" + }, + "outputs": [], + "source": [ + "sg, centroids = model.predict(image_paths[0], centroid_mode= True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "6WHXitp6FFzl" + }, + "source": [ + "## Visualizing the centroids which were determined by the model in Devolearn\n", + "\n", + "If you want to know visualize the number assigned to each centroid, uncomment the `cv2.putText` line" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "9sh0Ds2dxodR" + }, + "outputs": [], + "source": [ + "black = np.zeros(sg.shape)\n", + "\n", + "distance_matrix = np.zeros((len(centroids),len(centroids)))\n", + "\n", + "for i in range(len(centroids)):\n", + " black = cv2.circle(black, centroids[i], 5, color = (255,255,255), thickness = 2)\n", + " # black = cv2.putText(black, str(i), centroids[i], fontFace = cv2.FONT_HERSHEY_SIMPLEX, fontScale = 1, color = (255,255,255))\n", + "\n", + "for m in range(len(centroids)):\n", + " main = centroids[m]\n", + " for n in range(len(centroids)):\n", + " black = cv2.line(black, main, centroids[n], color = 255)\n", + " distance_matrix[m][n] = distance.euclidean(main, centroids[n])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 287 + }, + "colab_type": "code", + "id": "hhoV0MRYzuqf", + "outputId": "8eaddd92-4ac6-4a90-ce20-2abb3480afe7" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 362, + "metadata": { + "tags": [] + }, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light", + "tags": [] + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(black)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "pSW8QeyoGsoZ" + }, + "source": [ + "## The `distance_matrix`\n", + "\n", + "This matrix visualizes the distance between every \"node\" in form of a square matrix. Notice how the matrix is symmetric because the distance between node A and node is the same as node B to A. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 283 + }, + "colab_type": "code", + "id": "DN0b8OwordpD", + "outputId": "8e442d60-cfc3-473d-8016-cb9121fcc17f" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 364, + "metadata": { + "tags": [] + }, + "output_type": "execute_result" + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light", + "tags": [] + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(distance_matrix)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "urFg_ZnzHHW0" + }, + "source": [ + "## Scaling up the process for all the images \n", + "\n", + "If you want to visualize the nodes on a black image instead of the segmented contours, you can uncomment the `black = np.zeros(sg.shape)` line and comment out the `black = sg` line. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "S4bCNKtf2swY" + }, + "outputs": [], + "source": [ + "def make_node_map(image_path):\n", + " sg, centroids = model.predict(image_path, centroid_mode= True)\n", + " # black = np.zeros(sg.shape)\n", + " black = sg\n", + " real = cv2.imread(image_path,0)\n", + "\n", + " distance_matrix = np.zeros((len(centroids),len(centroids)))\n", + "\n", + " for i in range(len(centroids)):\n", + " black = cv2.circle(black, centroids[i], 5, thickness = 2, color = (255,255,255))\n", + " # black = cv2.putText(black, str(i), centroids[i], fontFace = cv2.FONT_HERSHEY_SIMPLEX, fontScale = 1, color = (255,255,255))\n", + "\n", + " for m in range(len(centroids)):\n", + " main = centroids[m]\n", + " for n in range(len(centroids)):\n", + " black = cv2.line(black, main, centroids[n], color = 255, thickness = 1)\n", + " distance_matrix[m][n] = distance.euclidean(main, centroids[n])\n", + "\n", + " \n", + " return real ,black, distance_matrix" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 263 + }, + "colab_type": "code", + "id": "o6aLp87ltYN3", + "outputId": "a84721bc-a656-406c-e57c-4e88f5684f91" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 368, + "metadata": { + "tags": [] + }, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light", + "tags": [] + }, + "output_type": "display_data" + } + ], + "source": [ + "real, nodes , map = make_node_map(image_paths[50])\n", + "\n", + "fig, ax = plt.subplots(1,3, figsize = (12,15))\n", + "\n", + "ax.flat[0].imshow(real)\n", + "ax.flat[1].imshow(nodes)\n", + "ax.flat[2].imshow(map)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "WL6jBqMFHocK" + }, + "source": [ + "## Creating an animation to better visualize the node maps\n", + "\n", + "All the frames would be saved in the `animation` folder" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "fgqTwBFgkf4E" + }, + "outputs": [], + "source": [ + "!rm -rf animation\n", + "!mkdir animation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "zU0l9kT539I_" + }, + "outputs": [], + "source": [ + "count = 0\n", + "for path in image_paths:\n", + " print(path)\n", + "\n", + " real, nodes,map = make_node_map(path)\n", + "\n", + " fig, ax = plt.subplots(1,3, figsize = (12,5))\n", + "\n", + " ax.flat[0].imshow(real)\n", + " ax.flat[1].imshow(nodes)\n", + " ax.flat[2].imshow(map)\n", + "\n", + "\n", + " ax.flat[0].set_xlabel('real', fontsize = 15)\n", + " ax.flat[1].set_xlabel('node map', fontsize = 15)\n", + " ax.flat[2].set_xlabel('distance matrix', fontsize = 15)\n", + "\n", + "\n", + " \n", + " clear_output(wait = True)\n", + " fig.savefig(\"animation/\" + str(count) + \".jpg\")\n", + " count += 1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "BGN5LSU8s6kL" + }, + "outputs": [], + "source": [ + "from PIL import Image" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 35 + }, + "colab_type": "code", + "id": "r0NJzXVB4WJF", + "outputId": "ac890498-81a3-43aa-b43b-f156cb16fc12" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "95\n" + ] + } + ], + "source": [ + "names = [ \"animation/\" + str(i) + \".jpg\" for i in range (0, count, 1)]\n", + "images = []\n", + "for n in names:\n", + " frame = Image.open(n)\n", + " images.append(frame)\n", + "print(len(images))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "9fMDMdwns5TJ" + }, + "outputs": [], + "source": [ + "images[0].save('nodes_matrix_long_smooth.gif',\n", + " save_all=True,\n", + " append_images=images[1:],\n", + " duration=150,\n", + " loop=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "s07ZVcn5JVCn" + }, + "source": [ + "## Saving the extracted centroids into a CSV file " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "BMWXtj3m07x_" + }, + "outputs": [], + "source": [ + "centroids = []\n", + "for i in range(len(image_paths)):\n", + " sg, centroid = model.predict(image_paths[i], centroid_mode= True)\n", + " centroids.append([centroid])\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "wsLCU5pc1ND_" + }, + "outputs": [], + "source": [ + "df = pd.DataFrame(centroids)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "C-dpPFpq1hQj" + }, + "outputs": [], + "source": [ + "df.columns = [\"centroids (x, y)\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 194 + }, + "colab_type": "code", + "id": "Ko6qXVUm1t3_", + "outputId": "9cfc8a71-c4c8-40d0-90b9-57ac204c3b70" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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centroids (x, y)
0[(184, 174), (270, 141), (113, 78), (92, 131),...
1[(112, 198), (183, 175), (271, 140), (91, 129)...
2[(184, 180), (271, 140), (90, 126), (191, 82)]
3[(91, 179), (182, 185), (273, 140), (92, 124),...
4[(178, 186), (273, 138), (93, 123), (198, 89)]
\n", + "
" + ], + "text/plain": [ + " centroids (x, y)\n", + "0 [(184, 174), (270, 141), (113, 78), (92, 131),...\n", + "1 [(112, 198), (183, 175), (271, 140), (91, 129)...\n", + "2 [(184, 180), (271, 140), (90, 126), (191, 82)]\n", + "3 [(91, 179), (182, 185), (273, 140), (92, 124),...\n", + "4 [(178, 186), (273, 138), (93, 123), (198, 89)]" + ] + }, + "execution_count": 378, + "metadata": { + "tags": [] + }, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "sFd_ZcZ01-2u" + }, + "outputs": [], + "source": [ + "df.to_csv(\"c_elegans_centroids.csv\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "j_BL1wPZJd1k" + }, + "source": [ + "# Moving on towards the next objective\n", + "\n", + "i.e trying to make a 3d model of the C. elegans embryo using images from n different planes of the same embryo" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "5FqbcSrCmKrS" + }, + "outputs": [], + "source": [ + "df = pd.read_csv(\"metadata.csv\")\n", + "image_paths = df[df[\"image\"].str.contains(\"real_45\") == True][\"image\"].unique()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "2TkTaf44XV7a" + }, + "outputs": [], + "source": [ + "centroids = []\n", + "for i in range(len(image_paths)):\n", + " sg, centroid = model.predict(image_paths[i], centroid_mode= True)\n", + " centroids.append(centroid)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "3kxxXP_CYMGs" + }, + "outputs": [], + "source": [ + "centroids = np.array(centroids)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "8vOJ_mxFLffD" + }, + "source": [ + "## Mapping the centroids into a 3d plot for visualization\n", + "\n", + "For our case, we do not use all the centroids, this was done in order regulate the density of the scatterplot. Try tweaking the step size in the for loop for a denser plot. " + ] + }, + { + "cell_type": "code", + "execution_count": 397, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "EJuIhKE1ZlfO" + }, + "outputs": [], + "source": [ + "x_s = []\n", + "y_s = []\n", + "z_s = []\n", + "\n", + "for i in range(0,len(centroids),15):\n", + " x,y = [list(c) for c in zip(*centroids[i])]\n", + " z = np.ones(len(x))*i\n", + "\n", + " x_s.extend(x)\n", + " y_s.extend(y)\n", + " z_s.extend(z)" + ] + }, + { + "cell_type": "code", + "execution_count": 399, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 247 + }, + "colab_type": "code", + "id": "wIN1ym4rcTCx", + "outputId": "2e396b85-f7f7-4a6e-effd-3b50b4d196e7" + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light", + "tags": [] + }, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "fig = plt.figure()\n", + "ax = fig.add_subplot(111, projection='3d')\n", + "ax.set_xlim(0, 350)\n", + "ax.set_ylim(0, 250)\n", + "\n", + "ax.scatter(x_s,y_s,z_s, cmap = \"jet\", marker = \"o\", s = 55)\n", + "ax.view_init(30, 20)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "colab_type": "text", + "id": "9AfWgkr8MyiJ" + }, + "source": [ + "## Making an animation \n", + "\n", + "The animation would help us visualize the 3d node map from different angles. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "znbjNLpldIpT" + }, + "outputs": [], + "source": [ + "from matplotlib import animation" + ] + }, + { + "cell_type": "code", + "execution_count": 394, + "metadata": { + "colab": {}, + "colab_type": "code", + "id": "V0E720hAc_pK" + }, + "outputs": [], + "source": [ + "def rotate(angle):\n", + " ax.view_init(elev = angle//5, azim=angle) ## x y plane angle \n", + "\n", + " if angle < 100:\n", + " ax.set_zlim(0, int((angle/100) * 90)) ## z elevation upto 100th frame\n", + "\n", + "rot_animation = animation.FuncAnimation(fig, rotate, frames=np.arange(0,150,1),interval=75)\n", + "rot_animation.save('3d_node_map.gif', dpi=80, writer='pillow')" + ] + } + ], + "metadata": { + "colab": { + "collapsed_sections": [], + "name": "experiments_with_devolearn.ipynb", + "provenance": [], + "toc_visible": true + }, + "kernelspec": { + "display_name": "Python 3", + "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": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +}