agumentation_for_object_detection (1).ipynb

{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"agumentation_for_object_detection.ipynb","provenance":[],"collapsed_sections":["z2dKzWbFZwr4","_9lI-BQWENdu","SuOUEtGKAI7c"]},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","source":["# Reference\n","https://towardsdatascience.com/data-augmentation-compilation-with-python-and-opencv-b76b1cd500e0\n","\n","https://github.com/usmanr149/Yolo_bbox_manipulation"],"metadata":{"id":"zP8_-qYv_w2-"}},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount(\"/content/drive\", force_remount=True)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"arUUSvN8_TW2","executionInfo":{"status":"ok","timestamp":1647333876479,"user_tz":-420,"elapsed":5135,"user":{"displayName":"Đức Phú Trần","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjg4aJfGCOz_wxJuZw490fjXu3RGKprvkZuoXLUww=s64","userId":"04672721089491963349"}},"outputId":"732db917-6b69-44df-f4c3-7dea62763506"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}]},{"cell_type":"markdown","source":["# Utility function\n","- yoloFormattocv\n","- cvFormattoYolo\n","- train_test_split"],"metadata":{"id":"z2dKzWbFZwr4"}},{"cell_type":"code","source":["#convert from Yolo_mark to opencv format\n","def yoloFormattocv(x1, y1, x2, y2, H, W):\n","    bbox_width = x2 * W\n","    bbox_height = y2 * H\n","    center_x = x1 * W\n","    center_y = y1 * H\n","\n","    voc = []\n","\n","    voc.append(center_x - (bbox_width / 2))\n","    voc.append(center_y - (bbox_height / 2))\n","    voc.append(center_x + (bbox_width / 2))\n","    voc.append(center_y + (bbox_height / 2))\n","\n","    return [int(v) for v in voc]\n","\n","# convert from opencv format to yolo format\n","# H,W is the image height and width\n","def cvFormattoYolo(corner, H, W):\n","    bbox_W = corner[3] - corner[1]\n","    bbox_H = corner[4] - corner[2]\n","\n","    center_bbox_x = (corner[1] + corner[3]) / 2\n","    center_bbox_y = (corner[2] + corner[4]) / 2\n","\n","    return corner[0], round(center_bbox_x / W, 6), round(center_bbox_y / H, 6), round(bbox_W / W, 6), round(bbox_H / H,6)"],"metadata":{"id":"9QnWgOSJNrwE"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# train - valid - test split\n","def train_test_split(path, val = 0, test = 0):\n","  import os\n","  import random\n","  import shutil\n","  assert val + test < 1\n","  save_dir = os.path.join(path,\"split_dataset\")\n","  if os.path.exists(save_dir):\n","    shutil.rmtree(save_dir)\n","  os.mkdir(save_dir)\n","  os.mkdir(os.path.join(save_dir,\"train\"))\n","  if val != 0:\n","    os.mkdir(os.path.join(save_dir,\"valid\"))\n","  if test != 0:\n","    os.mkdir(os.path.join(save_dir,\"test\"))\n","  all_file = os.listdir(path)\n","  all_image = []\n","  for file_name in all_file: \n","    if file_name.endswith(\".jpg\") or file_name.endswith(\".png\") or file_name.endswith(\".JPG\") or file_name.endswith(\".PNG\"):\n","      all_image.append(file_name)\n","  print(len(all_image))\n","  print(all_image)\n","  random.shuffle(all_image)\n","  train_len = round((1-val-test)*len(all_image))\n","  print(\"train_len: \",train_len)\n","  val_len = round(val * len(all_image))\n","  print(\"val_len: \",val_len)\n","  test_len = round(test * len(all_image))\n","  print(\"test_len: \",test_len)\n","  for i in range(len(all_image)):\n","    if (i < train_len):\n","      shutil.copy(os.path.join(path,all_image[i]),os.path.join(save_dir,\"train\",all_image[i]))\n","      shutil.copy(os.path.join(path,all_image[i][:-3] + \"txt\"),os.path.join(save_dir,\"train\",all_image[i][:-3] + \"txt\"))\n","    elif (i >= train_len and i < train_len + val_len):\n","      shutil.copy(os.path.join(path,all_image[i]),os.path.join(save_dir,\"valid\",all_image[i]))\n","      shutil.copy(os.path.join(path,all_image[i][:-3] + \"txt\"),os.path.join(save_dir,\"valid\",all_image[i][:-3] + \"txt\"))\n","    else:\n","      shutil.copy(os.path.join(path,all_image[i]),os.path.join(save_dir,\"test\",all_image[i]))\n","      shutil.copy(os.path.join(path,all_image[i][:-3] + \"txt\"),os.path.join(save_dir,\"test\",all_image[i][:-3] + \"txt\"))"],"metadata":{"id":"VfV9jONHNg1H"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["# All the augment\n"," - Add noise\n"," - Adjust brightness\n"," - Adjust saturate\n"," - Random cutout\n"," - Rotate image\n"," - Blur image\n"," - Reduce resolution\n"],"metadata":{"id":"_9lI-BQWENdu"}},{"cell_type":"code","source":["import numpy as np\n","import cv2\n","import os\n","import argparse\n","\n","class imageAgument:\n","    def __init__(self, dir_name, save_path =\"\", label = True):\n","        \"\"\" Image Augmentnh Oject \n","        Parameters\n","        --------------------\n","        dir_name : string\n","          Path to the image folder\n","        save_path : string\n","          Path to save folder\n","        label : bool\n","          If set to False, only image will be augment and save in the save_path.\n","          If set to True, label will be augment and save along side image. \n","          Label have yolo format and have to be in the same folder as the image.\n","        \"\"\"\n","        assert os.path.exists(dir_name), \"Invalid image path\"\n","        if os.path.isfile(dir_name):\n","          image_name = dir_name.split(\"/\")[-1]\n","          dir_path = \"\"\n","          for component in dir_name.split(\"/\")[:-1]:\n","            dir_path += component+\"/\"\n","          self._dir_name = dir_path\n","          self._list_file = [image_name]\n","        else:\n","          self._dir_name = dir_name\n","          self._list_file = os.listdir(dir_name)\n","        image_list = []\n","        # Extract jpg and png image file \n","        for file_name in self._list_file:\n","          if file_name.endswith(\".jpg\") or file_name.endswith(\".png\") or file_name.endswith(\".JPG\") or file_name.endswith(\".PNG\"):\n","            image_list.append(file_name)\n","        self._list_file = image_list\n","        self._label = label\n","        assert save_path == \"\" or os.path.exists(save_path), \"Invalid save path\"\n","        self._save_path = save_path\n","\n","    def __create_and_save(self, augment_name, arg):\n","        \"\"\" Create foler to save augment result\n","        Parameters\n","        -------------------\n","        augment_name : string\n","          Name of the augment in string\n","        arg\n","          Argument for the augment\n","        \"\"\"\n","        from shutil import copy\n","\n","        if self._save_path == \"\":\n","          save_path = os.path.join((self._dir_name),augment_name + \"_\" + str(arg))\n","          if os.path.exists(save_path):\n","            list_file = os.listdir(save_path)\n","            for file_name in list_file:\n","              os.remove(os.path.join(save_path,file_name))\n","            os.rmdir(save_path)\n","          os.mkdir(save_path)\n","        else:\n","          save_path = self._save_path\n","        \n","        count = 0\n","        for file_name in self._list_file:\n","          count += 1\n","          self._image = cv2.imread(os.path.join((self._dir_name),file_name))   \n","          if augment_name == \"noise\":\n","            result = self.__noise_img()\n","          if augment_name == \"blur\":\n","            result = self.__blur_img()            \n","          if augment_name == \"brightness\":\n","            result = self.__brightness_img()\n","          if augment_name == \"saturate\":\n","            result = self.__saturate_img()\n","          if augment_name == \"cutout\":\n","            result = self.__cutout_image(file_name)\n","          if augment_name == \"reduce_resolution\":\n","            result = self.__reduce_resolution_image()\n","          cv2.imwrite(os.path.join(save_path,file_name[:-4]+'_' + augment_name + \"_\" + str(arg) + '.jpg'),result)\n","          if self._label == True:\n","            copy(os.path.join(self._dir_name,file_name[:-4]+\".txt\"),os.path.join(save_path,file_name[:-4]+'_'+augment_name + \"_\" + str(arg) + '.txt'))\n","\n","        print(augment_name + \"_\" + str(arg) + \" : \" + str(count) + \" images\")\n","\n","    def __rotateYolobbox(self,image):\n","\n","        new_height, new_width = self.__rotate_image(image).shape[:2]\n","\n","        f = open(self._file_name + '.txt', 'r')\n","\n","        f1 = f.readlines()\n","\n","        new_bbox = []\n","\n","        H, W = image.shape[:2]\n","\n","        for x in f1:\n","            bbox = x.strip('\\n').split(' ')\n","            if len(bbox) > 1:\n","                (center_x, center_y, bbox_width, bbox_height) = yoloFormattocv(float(bbox[1]), float(bbox[2]),\n","                                                                               float(bbox[3]), float(bbox[4]), H, W)\n","\n","                upper_left_corner_shift = (center_x - W / 2, -H / 2 + center_y)\n","                upper_right_corner_shift = (bbox_width - W / 2, -H / 2 + center_y)\n","                lower_left_corner_shift = (center_x - W / 2, -H / 2 + bbox_height)\n","                lower_right_corner_shift = (bbox_width - W / 2, -H / 2 + bbox_height)\n","\n","                new_lower_right_corner = [-1, -1]\n","                new_upper_left_corner = []\n","\n","                for i in (upper_left_corner_shift, upper_right_corner_shift, lower_left_corner_shift,\n","                          lower_right_corner_shift):\n","                    new_coords = np.matmul(self._rot_matrix, np.array((i[0], -i[1])))\n","                    x_prime, y_prime = new_width / 2 + new_coords[0], new_height / 2 - new_coords[1]\n","                    if new_lower_right_corner[0] < x_prime:\n","                        new_lower_right_corner[0] = x_prime\n","                    if new_lower_right_corner[1] < y_prime:\n","                        new_lower_right_corner[1] = y_prime\n","\n","                    if len(new_upper_left_corner) > 0:\n","                        if new_upper_left_corner[0] > x_prime:\n","                            new_upper_left_corner[0] = x_prime\n","                        if new_upper_left_corner[1] > y_prime:\n","                            new_upper_left_corner[1] = y_prime\n","                    else:\n","                        new_upper_left_corner.append(x_prime)\n","                        new_upper_left_corner.append(y_prime)\n","\n","                new_bbox.append([bbox[0], new_upper_left_corner[0], new_upper_left_corner[1],\n","                                 new_lower_right_corner[0], new_lower_right_corner[1]])\n","\n","        return new_bbox\n","\n","    def __rotate_image(self,image):\n","        \"\"\"\n","        Rotates an image (angle in degrees) and expands image to avoid cropping\n","        Parameters\n","        -------------------\n","        label : bool\n","          Have the image been labeled and the label file must be put in the same folder as the the image\n","        Returns\n","        -------------------\n","          Image rotated\n","        \"\"\"\n","        height, width = image.shape[:2]  # image shape has 3 dimensions\n","        image_center = (width / 2, height / 2)  # getRotationMatrix2D needs coordinates in reverse order (width, height) compared to shape\n","\n","        rotation_mat = cv2.getRotationMatrix2D(image_center, self._angle, 1.)\n","\n","        # rotation calculates the cos and sin, taking absolutes of those.\n","        abs_cos = abs(rotation_mat[0, 0])\n","        abs_sin = abs(rotation_mat[0, 1])\n","\n","        # find the new width and height bounds\n","        bound_w = int(height * abs_sin + width * abs_cos)\n","        bound_h = int(height * abs_cos + width * abs_sin)\n","\n","        # subtract old image center (bringing image back to origin) and adding the new image center coordinates\n","        rotation_mat[0, 2] += bound_w / 2 - image_center[0]\n","        rotation_mat[1, 2] += bound_h / 2 - image_center[1]\n","\n","        # rotate image with the new bounds and translated rotation matrix\n","        rotated_img = cv2.warpAffine(image, rotation_mat, (bound_w, bound_h))\n","        return rotated_img\n","\n","    def rotate_folder(self, angle):\n","        \"\"\"\n","        Rotates an images in a folder (angle in degrees) and expands image to avoid cropping\n","        Parameters\n","        -------------------\n","        label : bool\n","          Have the image been labeled and the label file must be put in the same folder as the the image\n","        \"\"\"\n","        self._angle = angle\n","\n","        if self._save_path == \"\":\n","          save_path = os.path.join((self._dir_name),\"rotate_\" + str(angle))\n","          if os.path.exists(save_path):\n","            list_file = os.listdir(save_path)\n","            for file_name in list_file:\n","              os.remove(os.path.join(save_path,file_name))\n","            os.rmdir(save_path)\n","          os.mkdir(save_path)\n","        else:\n","          save_path = self._save_path        \n","\n","        rotation_angle = self._angle * np.pi / 180\n","        self._rot_matrix = np.array(\n","            [[np.cos(rotation_angle), -np.sin(rotation_angle)], [np.sin(rotation_angle), np.cos(rotation_angle)]])\n","        \n","        count = 0\n","        for file_name in self._list_file:\n","          count += 1\n","          image_name = file_name[:-4]    \n","          image_ext = file_name[-4:]\n","\n","          self._image_name = image_name\n","          self._image_ext = image_ext\n","          self._file_name = os.path.join((self._dir_name),image_name)\n","          \n","\n","          # Read image using cv2\n","          origin_image = cv2.imread(os.path.join(self._dir_name,image_name + image_ext), 1)\n","\n","          image = self.__rotate_image(origin_image)\n","\n","          # to write rotateed image to disk\n","          cv2.imwrite(os.path.join(save_path, image_name + '_' + 'rotated_'+ str(angle) + '.jpg'), image)\n","          \n","\n","          if self._label == True:\n","            bbox = self.__rotateYolobbox(origin_image)\n","            file_name = os.path.join(save_path, image_name+'_' + 'rotated_' + str(angle) + '.txt')\n","            if os.path.exists(file_name):\n","                os.remove(file_name)\n","\n","            # to write the new rotated bboxes to file\n","            for i in bbox:\n","                with open(file_name, 'a') as fout:\n","                    fout.writelines(\n","                        ' '.join(map(str, cvFormattoYolo(i, image.shape[0], image.shape[1]))) + '\\n')\n","        print('rotated_' + str(angle) + \" : \" + str(count) + \" images\")\n","\n","    def __blur_img(self):\n","        from PIL import Image, ImageFilter\n","        from PIL.Image import fromarray\n","        import numpy as np\n","        img = self._image\n","        img = fromarray(img.astype(\"uint8\"))\n","        result = img.filter(ImageFilter.GaussianBlur(radius = self._radius))\n","        result = np.asarray(result,dtype = \"uint8\")\n","\n","        return result\n","\n","    def blur_folder(self, radius):\n","        \"\"\"Blur Image by pixel.\n","          Parameters\n","          ------------             \n","          radius : int\n","              number of pixel around the center to be avarage\n","        \"\"\"\n","        from shutil import copy\n","        from PIL import Image, ImageFilter\n","        self._radius = radius        \n","        self.__create_and_save(\"blur\",radius)\n","\n","    def __noise_img(self):    \n","        from skimage.util import random_noise\n","\n","        #convert image to RGB format\n","        img = self._image\n","        after_img = random_noise(img,self._mode,self._seed)\n","\n","        # #multiply by 255 because random_noise return ndarray with the scale 1\n","        original_image = after_img*255\n","\n","        return original_image\n","\n","    def add_noise_folder(self, mode = \"pepper\",seed = None):\n","        \"\"\"Add random noise of various types to a floating-point image.\n","        Parameters\n","        ----------\n","        mode : str, optional\n","            One of the following strings, selecting the type of noise to add:\n","\n","            ‘gaussian’ Gaussian-distributed additive noise.\n","\n","            ‘localvar’ Gaussian-distributed additive noise, with specified\n","            local variance at each point of image.\n","\n","            ‘poisson’ Poisson-distributed noise generated from the data.\n","\n","            ‘salt’ Replaces random pixels with 1.\n","\n","            ‘pepper’ Replaces random pixels with 0 (for unsigned images) or\n","            -1 (for signed images).\n","\n","            ‘s&p’ Replaces random pixels with either 1 or low_val, where\n","            low_val is 0 for unsigned images or -1 for signed images.\n","\n","            ‘speckle’ Multiplicative noise using out = image + n*image, where\n","            n is Gaussian noise with specified mean & variance.\n","\n","        seed : int, optional\n","            If seed is None the numpy.random.Generator singleton is used. \n","            If seed is an int, a new Generator instance is used, seeded with seed. If seed is already a Generator instance then that instance is used.\n","            This will set the random seed before generating noise, for valid pseudo-random comparisons.\n","        \"\"\"\n","        self._mode = mode\n","        self._seed = seed        \n","        self.__create_and_save(\"noise\",self._mode)\n","\n","    def __brightness_img(self):\n","      from PIL import Image,ImageEnhance\n","      from PIL.Image import fromarray\n","      import numpy as np\n","\n","      img = self._image\n","      img = fromarray(img.astype(\"uint8\"))\n","      img_brightness_obj=ImageEnhance.Brightness(img)\n","      result = img_brightness_obj.enhance(self._factor)\n","      result = np.asarray(result,dtype = \"uint8\")\n","\n","      return result\n","\n","    def adjust_brightness_folder(self, factor):\n","      \"\"\"Add or reduce image brightness\n","      Parameters\n","      -----------------\n","      factor : float\n","        factor > 1  Brightness of Image increases according to given factor\n","        factor < 1  Brightness of Image decreases according to given factor\n","        factor = 1  Brightness of Image remains same\n","      \"\"\"\n","      self._factor = factor\n","      self.__create_and_save(\"brightness\",factor)\n","\n","    def __saturate_img(self):\n","      from PIL import Image,ImageEnhance\n","      from PIL.Image import fromarray\n","      import numpy as np\n","\n","      img = self._image\n","      img = fromarray(img.astype(\"uint8\"))\n","      img_brightness_obj=ImageEnhance.Color(img)\n","      result = img_brightness_obj.enhance(self._factor)\n","      result = np.asarray(result,dtype = \"uint8\")\n","\n","      return result\n","\n","    def adjust_saturate_folder(self, factor):\n","      \"\"\"Adjust image saturate\n","      Parameters\n","      -----------------\n","      factor : float\n","        factor > 1  Saturation of Image increases according to given factor\n","        factor < 1  Saturation of Image decreases according to given factor\n","        factor = 1  Saturation of Image remains same\n","      \"\"\"\n","      self._factor = factor\n","      self.__create_and_save(\"saturate\",factor)\n","\n","    def __cutout_image(self, file_image):      \n","      import random\n","      out = self._image.copy()\n","\n","      with open(os.path.join((self._dir_name),file_image[:-3]+\"txt\"), \"r\") as f_in:\n","        bounding_boxs = f_in.read().splitlines()\n","        for box in bounding_boxs:\n","          coords = box.split(\" \")\n","          min_x, min_y, max_x, max_y = yoloFormattocv(float(coords[1]),float(coords[2]),float(coords[3]),float(coords[4]),\n","                                                      self._image.shape[0], self._image.shape[1])\n","          mask_w = int((max_x - min_x)*self._percent)\n","          mask_h = int((max_y - min_y)*self._percent)\n","          mask_x1 = random.randint(min_x, max_x - mask_w)\n","          mask_y1 = random.randint(min_y, max_y - mask_h)\n","          mask_x2 = mask_x1 + mask_w\n","          mask_y2 = mask_y1 + mask_h\n","          cv2.rectangle(out, (mask_x1, mask_y1), (mask_x2, mask_y2), (0, 0, 0), thickness=-1)\n","      return out\n","\n","    def random_cutout_folder(self, size_box_to_cut = 0.2):\n","      \"\"\" Cutout random box in every bounding box\n","      Parameters\n","      ------------------------- \n","      size_box_to_cut : float\n","        Size of the box to cut\n","      \"\"\"\n","      self._percent = size_box_to_cut      \n","      self.__create_and_save(\"cutout\",size_box_to_cut)\n","\n","    def __reduce_resolution_image(self):\n","      from PIL import Image\n","      keep_resolution = self._keep_resolution\n","      im = Image.fromarray(self._image.astype(\"uint8\"))\n","      orig_size = im.size\n","      width, height = orig_size\n","      # open_cv_image = im\n","      # open_cv_image = open_cv_image[:, :, ::-1].copy()\n","\n","      im.thumbnail([width*keep_resolution, height*keep_resolution])\n","      # open_cv_image = numpy.array(im)\n","      # open_cv_image = open_cv_image[:, :, ::-1].copy()\n","      im = im.transform(orig_size, Image.EXTENT, (0,0, width*keep_resolution, height*keep_resolution))\n","      open_cv_image = np.asarray(im, dtype = \"uint8\")\n","      # open_cv_image = open_cv_image[:, :, ::-1].copy()\n","      return open_cv_image\n","        \n","    def reduce_resolution_folder(self, keep_resolution = 0.7):\n","      \"\"\" Reduce resolution of the image\n","      Parameters\n","      ------------------------- \n","      keep_resolution : float\n","        Proportion of the image to be kept\n","      \"\"\"\n","      self._keep_resolution = keep_resolution      \n","      self.__create_and_save(\"reduce_resolution\",keep_resolution)\n","\n","        \n","                  \n","\n","\n"],"metadata":{"id":"heqKiKzONr1w"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["# Test"],"metadata":{"id":"QvyoU7Mpmy6L"}},{"cell_type":"code","source":["# set path to the image or folder for augment and path to save folder then choose the augment\n","# augmented folder will be save in the save path\n","# if save path is not given. It will be automatically save in a sub-folder of the image folder\n","\n","image_path = \"/content/drive/MyDrive/Colab Notebooks/front_cmnd_aligned\"\n","save_path = \"/content/drive/MyDrive/Colab Notebooks/front_cmnd_aligned\"\n","\n","#test with 1 image\n","# image_path = \"/content/drive/MyDrive/Colab Notebooks/front_cmnd_aligned/CMND LE TUAN AN T.jpg\"\n","# save_path = \"\"\n","\n","\n","imageAgument(image_path,save_path).reduce_resolution_folder(0.9)\n","imageAgument(image_path,save_path).rotate_folder(3)\n","imageAgument(image_path,save_path).rotate_folder(-3)\n","imageAgument(image_path,save_path).add_noise_folder(\"gaussian\")\n","imageAgument(image_path,save_path).blur_folder(2)\n","imageAgument(image_path,save_path).random_cutout_folder(0.2)\n","imageAgument(image_path,save_path).adjust_brightness_folder(1.5)"],"metadata":{"id":"iP5FVgaotxBe","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1647328352922,"user_tz":-420,"elapsed":549345,"user":{"displayName":"Đức Phú Trần","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjg4aJfGCOz_wxJuZw490fjXu3RGKprvkZuoXLUww=s64","userId":"04672721089491963349"}},"outputId":"ef464ade-988b-4037-8bdd-0553e00ede3d"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["reduce_resolution_0.9 : 116 images\n","rotated_3 : 232 images\n","rotated_-3 : 464 images\n","noise_gaussian : 928 images\n","blur_2 : 1856 images\n","cutout_0.2 : 3712 images\n","brightness_1.5 : 7424 images\n"]}]},{"cell_type":"code","source":["# split_dataset folder will be save in the same folder\n","train_test_split(\"/content/drive/MyDrive/Colab Notebooks/front_cmnd_aligned\",val=0.1)"],"metadata":{"id":"6MPrU-EvviLT","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1647326843267,"user_tz":-420,"elapsed":19460,"user":{"displayName":"Đức Phú Trần","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gjg4aJfGCOz_wxJuZw490fjXu3RGKprvkZuoXLUww=s64","userId":"04672721089491963349"}},"outputId":"882fd7a9-f7a3-4f44-cc38-85b8c0e8a2d6"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["812\n","['cmnd_hoai_trang_11_reduce_resolution_0.9.jpg', 'cmnd_hng_xuan1_001_reduce_resolution_0.9.jpg', 'cmnd_ngan1_001_reduce_resolution_0.9.jpg', 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'IMG_2047_brightness_1.5.jpg', 'IMG_2045_brightness_1.5.jpg', 'IMG_2091_brightness_1.5.jpg', 'IMG_2077_brightness_1.5.jpg', 'IMG_2085_brightness_1.5.jpg', 'IMG_2029_brightness_1.5.jpg', 'IMG_2115_brightness_1.5.jpg', 'IMG_2211_brightness_1.5.jpg', 'IMG_2103_brightness_1.5.jpg', 'IMG_2031_brightness_1.5.jpg', 'IMG_2067_brightness_1.5.jpg', 'IMG_2034_brightness_1.5.jpg', 'IMG_2043_brightness_1.5.jpg', 'IMG_2151_brightness_1.5.jpg', 'IMG_2127_brightness_1.5.jpg', 'IMG_2197_brightness_1.5.jpg', 'IMG_2079_brightness_1.5.jpg']\n","train_len:  731\n","val_len:  81\n","test_len:  0\n"]}]},{"cell_type":"code","source":["import os\n","augment_path = \"/content/drive/MyDrive/Colab Notebooks/front_cmnd_aligned\"\n","images_path = augment_path + \"/images\"\n","# os.mkdir(images_path)\n","labels_path = augment_path + \"/labels\"\n","# os.mkdir(labels_path)\n","\n","# import shutil\n","# for file_name in os.listdir(augment_path):\n","#   if file_name.endswith(\".txt\") and file_name != \"classes.txt\":\n","#     shutil.move(os.path.join(augment_path,file_name),os.path.join(labels_path,file_name))\n","#   elif file_name.endswith(\".jpg\") or file_name.endswith(\".png\") or file_name.endswith(\".JPG\") or file_name.endswith(\".PNG\"):\n","#     shutil.move(os.path.join(augment_path,file_name),os.path.join(images_path,file_name))"],"metadata":{"id":"0ofd20igiZkK"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["## Show image with label"],"metadata":{"id":"SuOUEtGKAI7c"}},{"cell_type":"code","source":["import os\n","from PIL import Image\n","image_path = \"/content/image/cutout_0.3/IMG_2477_cutout_0.3.jpg\"\n","file_name = image_path[:-3] + \"txt\"\n","\n","im = Image.open(image_path)\n","width, height = im.size\n","\n","from skimage import data, io\n","from matplotlib import pyplot as plt\n","import matplotlib.patches as patches\n","import numpy as np\n","from PIL import Image\n","im = Image.open(image_path)\n","\n","origin_width, origin_height = im.size\n","\n","fig,ax = plt.subplots(1)\n","show_img = np.asarray(im)\n","io.imshow(show_img)\n","\n","\n","# Create a Rectangle patch\n","with open(file_name,\"r\") as f_out:\n","  lines = f_out.read().splitlines()\n","  for line in lines:\n","    component = line.split(\" \")\n","    new_annot = {\"x\":float(component[1]),\"y\":float(component[2]),\"width\":float(component[3]),\"height\":float(component[4])}\n","    height = new_annot[\"height\"] \n","    width = new_annot[\"width\"] \n","\n","    x = new_annot[\"x\"] - (width/2)\n","    y = new_annot[\"y\"] - (height/2)\n","    print(\"x \",x,\"y \",y, \"width \", width, \"height \", height)\n","    rect = patches.Rectangle((round(x*origin_width),round(y*origin_height)),\n","                             round(width* origin_width),round(height* origin_height),linewidth=5,edgecolor='b',facecolor='none')\n","\n","    # Add the patch to the Axes\n","    ax.add_patch(rect)\n","    \n","plt.show()\n","fig.savefig(\"result.jpg\")"],"metadata":{"id":"xOeIQaH5L6KP","outputId":"1e96798d-a0c6-46dc-8644-406510cb766d","colab":{"base_uri":"https://localhost:8080/","height":436}},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["x  0.05937500000000001 y  0.4041665 width  0.248438 height  0.483333\n","x  0.490625 y  0.25416700000000003 width  0.339062 height  0.1\n","x  0.42968700000000004 y  0.3437495 width  0.5125 height  0.104167\n","x  0.6281249999999999 y  0.5124995 width  0.317188 height  0.091667\n","x  0.6781250000000001 y  0.5895835 width  0.25625 height  0.091667\n","x  0.354687 y  0.677083 width  0.579688 height  0.1\n","x  0.689063 y  0.7666664999999999 width  0.257812 height  0.095833\n","x  0.38437499999999997 y  0.8374995 width  0.55625 height  0.097917\n"]},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["# import numpy\n","\n","# def find_coeffs(pa, pb):\n","#     matrix = []\n","#     for p1, p2 in zip(pa, pb):\n","#         matrix.append([p1[0], p1[1], 1, 0, 0, 0, -p2[0]*p1[0], -p2[0]*p1[1]])\n","#         matrix.append([0, 0, 0, p1[0], p1[1], 1, -p2[1]*p1[0], -p2[1]*p1[1]])\n","\n","#     A = numpy.matrix(matrix, dtype=numpy.float)\n","#     B = numpy.array(pb).reshape(8)\n","\n","#     res = numpy.dot(numpy.linalg.inv(A.T * A) * A.T, B)\n","#     return numpy.array(res).reshape(8)\n","\n","# import sys\n","# from PIL import Image\n","\n","# img = Image.open(\"/content/image/IMG_2477.jpg\")\n","# width, height = img.size\n","# horizon_shear = -0.3\n","# vertical_shear = 0\n","# xshift = abs(horizon_shear) * width\n","# new_width = width + int(round(xshift))\n","# # img = img.transform((new_width, height), Image.AFFINE,\n","# #         (1, m, -xshift if m > 0 else 0, 0, 1, 0), Image.BICUBIC)\n","\n","\n","# # img.save(\"IMG_2477.jpg\")\n","\n","# coeffs = find_coeffs([(0, 0), (width, 0), (new_width, height), (xshift, height)],\n","#         [(0, 0), (width, 0), (width, height), (0, height)]\n","#         )\n","\n","# img = img.transform((new_width, height), Image.PERSPECTIVE, coeffs,\n","#         Image.BICUBIC).save(\"IMG_2477_revert.jpg\")\n"],"metadata":{"id":"Ugp1qTIqE0dt","colab":{"base_uri":"https://localhost:8080/"},"outputId":"c1c029cd-413a-4548-b20a-cbf50c9c89bf"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:9: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n","Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n","  if __name__ == '__main__':\n"]}]},{"cell_type":"code","source":[""],"metadata":{"id":"AZsTU-pN-QTe"},"execution_count":null,"outputs":[]}]}