{"cells":[{"metadata":{"_kg_hide-output":true,"_kg_hide-input":true,"trusted":true},"cell_type":"code","source":"from IPython.core.display import HTML\nHTML(\"\"\"\n<style>\n@import url('https://fonts.googleapis.com/css2?family=Source+Code+Pro&display=swap');\n</style>\n\"\"\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# HuBMAP - Simple getting started with Image, Mask and Bounding Box\n<h4 style=\"font-family: 'Source Code Pro', monospace\">Version 9: Also contains how to generate the dataset on your own</h4>\n<a href=\"https://www.kaggle.com/ckanth090/hubmap-5185x256x256-image-and-masks\">Link to my dataset - contains 5185x256x256 images</a><br><br>\n\n\n### Contents\n1. [Glomerular Identification meaning](#Why-Glomelular-Identification-?)\n2. [Dataset and Goal](#Dataset-and-Goal)\n3. [Looking into one image](#Looking-into-one-random-image-from-the-train-dataset)\n4. [Decoding and adding the mask](#Decoding-and-adding-the-mask)\n5. [Get bounding boxes for all the glomeruli](#Get-bounding-boxes-for-all-the-glomeruli)\n6. [Vizualization](#There-we-go,-we-have-identified-a-Glomeruli,-it's-mask-and-it's-corresponding-BBOX)"},{"metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"cell_type":"code","source":"import collections\nimport json\nimport os\nimport uuid\n\nimport matplotlib.pyplot as plt\nimport numpy as np\nimport pandas as pd\nfrom PIL import Image, ImageDraw\nimport tifffile as tiff \nimport seaborn as sns\n\nfrom skimage.measure import label, regionprops\nimport cv2","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"<h1 style=\"font-family: 'Source Code Pro', monospace\">Why Glomelular Identification ?</h1>\n\n<span style=\"font-family: 'Source Code Pro', monospace\">Unless things go wrong, most of us don’t spend much time thinking about what it takes to urinate, but in fact, your kidneys and urinary system are quite amazing. Together they receive over a liter of blood each minute, and eliminate around 1.5 litres of urine per day, efficiently getting rid of excess water and waste products that would otherwise cause you some serious problems.</span>\n    \n<h3 style=\"font-family: 'Source Code Pro', monospace\">What is Glomelular filtration ?</h3>\n<span style=\"font-family: 'Source Code Pro', monospace\">Glomerular filtration is the first step in making urine. It is the process that your kidneys use to filter excess fluid and waste products out of the blood into the urine collecting tubules of the kidney, so they may be eliminated from your body.</span>\n\n![image.png](attachment:image.png)\nhttps://www.khanacademy.org/test-prep/mcat/organ-systems/the-renal-system/a/renal-physiology-glomerular-filtration","attachments":{"image.png":{"image/png":"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"}}},{"metadata":{},"cell_type":"markdown","source":"# Dataset and Goal\nThe dataset contains images of kidneys 11 fresh frozen and 9 Formalin Fixed Paraffin Embedded (FFPE) PAS kidney images. <br>\nThere can be over 600,000 glomeruli in each human kidney, each with a range from 100-350μm. <br>\n**Goal:** Develop segmentation algorithms that identify glomeruli in the PAS stained microscopy data.\n\n## Map of the training and testing images\n*8 train .tiff images* <br>\n*5 test .tiff images*"},{"metadata":{"_uuid":"d629ff2d2480ee46fbb7e2d37f6b5fab8052498a","_cell_guid":"79c7e3d0-c299-4dcb-8224-4455121ee9b0","trusted":true},"cell_type":"code","source":"! cd ../input/hubmap-kidney-segmentation/train && ls","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"TRAIN_PATH = \"../input/hubmap-kidney-segmentation/train/\"\nTEST_PATH = \"../input/hubmap-kidney-segmentation/test/\"\n## Extra dataset information about all the training images\ndataset_info = pd.read_csv(\"../input/hubmap-kidney-segmentation/HuBMAP-20-dataset_information.csv\")\nprint(dataset_info.shape)\ndataset_info.head(13).T","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Training dataset information\ntrain_df = pd.read_csv(\"../input/hubmap-kidney-segmentation/train.csv\")\ntrain_df.head().T # Contains the training image id and the RLE","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Looking into one random image from the train dataset"},{"metadata":{"trusted":true},"cell_type":"code","source":"train_df","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_df.iloc[4, 0]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_df['id'][4]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Looking into the anatomical_structure json files\nwith open(TRAIN_PATH + train_df.iloc[4, 0] + \"-anatomical-structure.json\") as f:\n    data = json.load(f)\n# print(json.dumps(data[0], indent=4, sort_keys=True))\nprint(data[0]) # Looking into the first Glomerulus coordinates","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"print(json.dumps(data[0], indent=4, sort_keys=True))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_df.iloc[1, 0]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Looking into the anatomical_structure json files\nwith open(TRAIN_PATH + train_df.iloc[1, 0] + \"-anatomical-structure.json\") as f:\n    data2 = json.load(f)\nprint(json.dumps(data2[0], indent=4, sort_keys=True))\n#print(data[0]) # Looking into the first Glomerulus coordinates","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"train_df.iloc[4, 0]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Looking into a single training image\nimage2 = tiff.imread(TRAIN_PATH + train_df.iloc[1, 0] + \".tiff\")\nprint(train_df.iloc[1, 0], \" training image with a shape of -->\", image2.shape)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Looking into a single training image\nimage1 = tiff.imread(TRAIN_PATH + train_df.iloc[4, 0] + \".tiff\")\nprint(train_df.iloc[4, 0], \" training image with a shape of -->\", image1.shape)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Looking into a single training image\nimage = tiff.imread(TRAIN_PATH + train_df.iloc[3, 0] + \".tiff\")\nprint(train_df.iloc[3, 0], \" training image with a shape of -->\", image.shape)","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## The kidney tissue image\nimage1 = image1[0][0].transpose(1, 2, 0)\nplt.figure(figsize=(10, 10))\nplt.imshow(image1)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## The kidney tissue image (medulla)\n#image2 = image2[0][0].transpose(1, 2, 0)\nplt.figure(figsize=(10, 10))\nplt.imshow(image2)\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"image1[0][0]","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nfrom IPython.display import Image\nprint(\"Figure: Glomerulus(Kidney)\")\nImage(filename=\"../input/kidney/72185-035-FCD687C7.jpg\")","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Decoding and adding the mask"},{"metadata":{"trusted":true},"cell_type":"code","source":"## We need to decode the mask from encoding column of train.csv\n## https://www.kaggle.com/paulorzp/rle-functions-run-lenght-encode-decode\ndef mask2rle(img):\n    '''\n    img: numpy array, 1 - mask, 0 - background\n    Returns run length as string formated\n    '''\n    pixels= img.T.flatten()\n    pixels = np.concatenate([[0], pixels, [0]])\n    runs = np.where(pixels[1:] != pixels[:-1])[0] + 1\n    runs[1::2] -= runs[::2]\n    return ' '.join(str(x) for x in runs)\n \ndef rle2mask(mask_rle, shape):\n    '''\n    mask_rle: run-length as string formated (start length)\n    shape: (width,height) of array to return \n    Returns numpy array, 1 - mask, 0 - background\n\n    '''\n    s = mask_rle.split()\n    starts, lengths = [np.asarray(x, dtype=int) for x in (s[0:][::2], s[1:][::2])]\n    starts -= 1\n    ends = starts + lengths\n    print(starts, ends)\n    img = np.zeros(shape[0]*shape[1], dtype=np.uint8)\n    for lo, hi in zip(starts, ends):\n        img[lo:hi] = 1\n    return img.reshape(shape).T","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Plot all the Glomeruli in this particular kidney\nmask1 = rle2mask(train_df.iloc[4, 1], (image1.shape[1], image1.shape[0])) # Call the RLE2Mask function","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## The same kidney image with all the masks\nplt.figure(figsize=(10, 10))\nplt.imshow(image1)\nplt.imshow(mask1, alpha=0.5, cmap='plasma')\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Get bounding boxes for all the Glomeruli"},{"metadata":{"trusted":true},"cell_type":"code","source":"## Identify all the coordinates of the glomeruli in this image\nlbl_0 = label(mask1) \nprops = regionprops(lbl_0)\nlen(props) ## There are 198 glomeruli's identified\nbboxes = [] ## Convert all the 198 items into bounding boxes so we can save these images for training\nfor prop in props:\n    bboxes.append([prop.bbox[0] - 30, prop.bbox[1] - 30, \n                   prop.bbox[2] + 30, prop.bbox[3] + 30]) ## Adding a little bit of extra image run","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## From the above algorithm we identify and plot a single glomeruli from the kidney\nplt.figure(figsize=(10, 10))\nplt.imshow(image1[bboxes[0][0]:bboxes[0][2], bboxes[0][1]:bboxes[0][3], :])\nplt.imshow(mask1[bboxes[0][0]:bboxes[0][2], bboxes[0][1]:bboxes[0][3]], alpha=0.5, cmap='plasma')\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"## There we go, we have identified a Glomeruli, it's mask and it's corresponding BBOX"},{"metadata":{"trusted":true},"cell_type":"code","source":"## Let's look into some more of these glomeruli\nfig, axes = plt.subplots(2, 5, figsize=(20, 8))\nval = 10\nfor i in range(2):\n    for j in range(5):\n        axes[i, j].imshow(image1[bboxes[val][0]:bboxes[val][2], bboxes[val][1]:bboxes[val][3], :]); val += 1\n        axes[i, j].axis('off')\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Glomeruli with masks\nfig, axes = plt.subplots(2, 5, figsize=(20, 8))\nval = 10\nfor i in range(2):\n    for j in range(5):\n        axes[i, j].imshow(image1[bboxes[val][0]:bboxes[val][2], bboxes[val][1]:bboxes[val][3], :])\n        axes[i, j].imshow(mask1[bboxes[val][0]:bboxes[val][2], bboxes[val][1]:bboxes[val][3]], alpha=0.5, cmap='plasma')\n        axes[i, j].axis('off'); val += 1\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## Only masks\nfig, axes = plt.subplots(2, 5, figsize=(20, 8))\nval = 10\nfor i in range(2):\n    for j in range(5): \n        axes[i, j].imshow(mask1[bboxes[val][0]:bboxes[val][2], bboxes[val][1]:bboxes[val][3]], cmap='gray')\n        axes[i, j].axis('off'); val += 1\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Generating the dataset"},{"metadata":{"trusted":true},"cell_type":"code","source":"## I will be only creating dataset for this one image, but you will have to create the data using all the 8 images\n## I will also be using the Albumentation package for generating image augmented data\nimport albumentations as A\n\naugment = A.Compose([\n    A.ShiftScaleRotate(),\n    A.HorizontalFlip(p=1),\n    A.CLAHE(p=1),\n    A.RandomRotate90(),\n    A.ElasticTransform(),\n], p=1)\n\naugmented = augment(image=image1[bboxes[3][0]:bboxes[3][2], bboxes[3][1]:bboxes[3][3], :], \\\n                    mask=mask1[bboxes[3][0]:bboxes[3][2], bboxes[3][1]:bboxes[3][3]]) ## Apply first transformation\naugmented2 = augment(image=image1[bboxes[3][0]:bboxes[3][2], bboxes[3][1]:bboxes[3][3], :], \\\n                    mask=mask1[bboxes[3][0]:bboxes[3][2], bboxes[3][1]:bboxes[3][3]]) ## Apply second transformation","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"## From the above algorithm we identify and plot a single glomeruli from the kidney\nfig, axes = plt.subplots(2, 3, figsize=(15, 8))\n\naxes[0, 0].imshow(image1[bboxes[3][0]:bboxes[3][2], bboxes[3][1]:bboxes[3][3], :]); axes[0, 0].axis('off')\naxes[1, 0].imshow(mask1[bboxes[3][0]:bboxes[3][2], bboxes[3][1]:bboxes[3][3]], cmap='gray'); axes[1, 0].axis('off')\n\naxes[0, 1].imshow(augmented['image']); axes[0, 1].axis('off')\naxes[1, 1].imshow(augmented['mask']); axes[1, 1].axis('off')\n\naxes[0, 2].imshow(augmented2['image']); axes[0, 2].axis('off')\naxes[1, 2].imshow(augmented2['mask']); axes[1, 2].axis('off')\n\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Reference 🏛\n\n[1] [Nayu.T.S's Visualization NB](https://www.kaggle.com/nayuts/hubmap-let-s-visualize-and-understand-dataset)"},{"metadata":{"trusted":true},"cell_type":"code","source":"","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"pygments_lexer":"ipython3","nbconvert_exporter":"python","version":"3.6.4","file_extension":".py","codemirror_mode":{"name":"ipython","version":3},"name":"python","mimetype":"text/x-python"}},"nbformat":4,"nbformat_minor":4}