data_series_detection.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from skimage import io, color\n",
    "from skimage.measure import label, regionprops\n",
    "from sklearn.cluster import KMeans\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import datasets\n",
    "import json\n",
    "import numpy as np\n",
    "from utils import *\n",
    "from matplotlib import pyplot as plt\n",
    "from roboflow import Roboflow\n",
    "from segment_anything import SamPredictor, sam_model_registry\n",
    "from helper_code.pipeline import run_pipeline\n",
    "import os\n",
    "import random\n",
    "from helper_code.full_extraction_pipeline import get_fast_bounding_box\n",
    "import cv2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "sam = sam_model_registry[\"default\"](checkpoint=\"../../../Downloads/sam_vit_h_4b8939.pth\")\n",
    "sam_predictor = SamPredictor(sam)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading Roboflow workspace...\n",
      "loading Roboflow project...\n"
     ]
    }
   ],
   "source": [
    "rf = Roboflow(ROBOFLOW_API_KEY)\n",
    "project = rf.workspace().project(\"final_annotation_classification\")\n",
    "model = project.version(1).model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "image_num = 19764"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Bounding Box in Image 19764')"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "image_name, boundingBox = get_fast_bounding_box(image_num, sam_predictor)\n",
    "\n",
    "image = cv2.imread(image_name)\n",
    "cv2.rectangle(image, boundingBox['topLeft'], boundingBox['bottomRight'], (0, 0, 255), 2)\n",
    "plt.imshow(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))\n",
    "plt.title(f'Bounding Box in Image {image_num}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'topLeft': [94, 7], 'bottomRight': [1064, 631]}"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boundingBox"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.cluster import KMeans\n",
    "from skimage import io\n",
    "from PIL import Image\n",
    "\n",
    "def create_mask(image, bounding_box):\n",
    "    \"\"\"\n",
    "    Create a binary mask from bounding box coordinates.\n",
    "    \n",
    "    Parameters:\n",
    "    - image: numpy array, the image for which the mask is created\n",
    "    - bounding_box: dict, contains \"topLeft\" and \"bottomRight\" keys with (x, y) coordinates\n",
    "    \n",
    "    Returns:\n",
    "    - mask: numpy array, binary mask where the bounding box area is 1 and the rest is 0\n",
    "    \"\"\"\n",
    "    print(f\"Image shape: {image.shape}\")\n",
    "    image_height, image_width, _ = image.shape\n",
    "\n",
    "    mask = np.zeros((image_height, image_width), dtype=np.uint8)\n",
    "    try:\n",
    "        x1, y1 = bounding_box[\"topLeft\"]\n",
    "        x2, y2 = bounding_box[\"bottomRight\"]\n",
    "    except KeyError as e:\n",
    "        raise ValueError(f\"Missing bounding box key: {e}\")\n",
    "    except ValueError as e:\n",
    "        raise ValueError(f\"Invalid bounding box coordinates: {e}\")\n",
    "    \n",
    "    if not all(isinstance(i, int) for i in [x1, y1, x2, y2]):\n",
    "        raise ValueError(\"Bounding box coordinates must be integers\")\n",
    "\n",
    "    # Ensure bounding box is within image dimensions\n",
    "    x1, x2 = np.clip([x1, x2], 0, image_width - 1)\n",
    "    y1, y2 = np.clip([y1, y2], 0, image_height - 1)\n",
    "\n",
    "    # Set the pixels within the bounding box to 1\n",
    "    mask[y1:y2+1, x1:x2+1] = 1\n",
    "    return mask\n",
    "\n",
    "def load_image(image_path):\n",
    "    image = io.imread(image_path)\n",
    "    print(f\"Loaded image shape: {image.shape}\")\n",
    "    return image\n",
    "\n",
    "def apply_mask(image, mask):\n",
    "    masked_image = image.copy()\n",
    "    if masked_image.ndim == 2:  # Grayscale image\n",
    "        masked_image[mask == 0] = 0\n",
    "    elif masked_image.shape[2] == 4:  # Image has 4 channels (RGBA)\n",
    "        alpha_channel = masked_image[:, :, 3]\n",
    "        for i in range(3):\n",
    "            channel = masked_image[:, :, i]\n",
    "            channel[mask == 0] = 0\n",
    "        masked_image[:, :, 3] = alpha_channel\n",
    "    else:  # Image is RGB\n",
    "        masked_image[mask == 0] = [0, 0, 0]\n",
    "    return masked_image\n",
    "\n",
    "def cluster_colors(image, n_clusters=5):\n",
    "    print(f\"Clustering colors in image with shape: {image.shape}\")\n",
    "    pixels = image.reshape(-1, image.shape[2])\n",
    "    non_white_mask = ~np.all(pixels[:, :3] == [255, 255, 255], axis=1)\n",
    "    non_white_pixels = pixels[non_white_mask]\n",
    "\n",
    "    print(f\"Number of non-white pixels: {non_white_pixels.shape[0]}\")\n",
    "\n",
    "    kmeans = KMeans(n_clusters=n_clusters, n_init='auto')\n",
    "    kmeans.fit(non_white_pixels)\n",
    "    \n",
    "    labels = kmeans.labels_\n",
    "    cluster_centers = kmeans.cluster_centers_\n",
    "\n",
    "    # Create an array to store the clustered image\n",
    "    clustered_image = np.zeros_like(pixels)\n",
    "    # Replace non-white pixels with their corresponding cluster centers\n",
    "    clustered_image[non_white_mask] = cluster_centers[labels].astype(int)\n",
    "    clustered_image = clustered_image.reshape(image.shape)\n",
    "    \n",
    "    return clustered_image, labels, cluster_centers, non_white_mask\n",
    "\n",
    "def separate_clusters(image, labels, cluster_centers, non_white_mask):\n",
    "    clusters = []\n",
    "    pixels = image.reshape(-1, image.shape[2])\n",
    "    \n",
    "    for cluster_idx, center in enumerate(cluster_centers):\n",
    "        cluster_image = np.zeros_like(pixels)\n",
    "        cluster_mask = (labels == cluster_idx)\n",
    "        cluster_image[non_white_mask] = np.where(cluster_mask[:, None], center, [255, 255, 255, 0])\n",
    "        cluster_image = cluster_image.reshape(image.shape)\n",
    "        clusters.append(cluster_image)\n",
    "    \n",
    "    return clusters\n",
    "\n",
    "def process_image(image_path, bounding_box, n_clusters=5):\n",
    "    image = load_image(image_path)\n",
    "    mask = create_mask(image, bounding_box)\n",
    "    masked_image = apply_mask(image, mask)\n",
    "    print(f\"Masked image shape: {masked_image.shape}\")\n",
    "    clustered_image, labels, cluster_centers, non_white_mask = cluster_colors(masked_image, n_clusters)\n",
    "    \n",
    "    clusters = separate_clusters(masked_image, labels, cluster_centers, non_white_mask)\n",
    "    \n",
    "    for idx, cluster in enumerate(clusters):\n",
    "        plt.imshow(cluster)\n",
    "        plt.title(f'Cluster {idx+1}')\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded image shape: (700, 1268, 4)\n",
      "Image shape: (700, 1268, 4)\n",
      "Masked image shape: (700, 1268, 4)\n",
      "Clustering colors in image with shape: (700, 1268, 4)\n",
      "Number of non-white pixels: 404322\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Call the function with your image and mask paths\n",
    "process_image('../plot_images/'+str(image_num)+'.png', boundingBox, 8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "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": "3.9.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}