#pragma once #include #include #include #include #include "dl_define.hpp" #include "dl_variable.hpp" #include "dl_math_matrix.hpp" namespace dl { namespace image { typedef enum { IMAGE_RESIZE_BILINEAR = 0, /*> 7; return DL_CLIP(temp, 0, 255); } /** * @brief Convert RGB565 pixel to RGB888. * * @tparam T supports all integer types * @param input pixel value in RGB565 * @param output pixel value in RGB888 */ template inline void convert_pixel_rgb565_to_rgb888(uint16_t input, T *output) { output[0] = (input & 0x1F00) >> 5; // blue output[1] = ((input & 0x7) << 5) | ((input & 0xE000) >> 11); // green output[2] = input & 0xF8; // red } /** * @brief Convert RGB565 image to RGB888 image. * * @param image ptr of RGB565 image * @param image_shape shape of the input image * @return Tensor* output RGB88 image */ Tensor *convert_image_rgb565_to_rgb888(uint16_t *image, std::vector &image_shape); /** * @brief Convert RGB565 pixel to Gray. * * @param input pixel value in RGB565 * @return pixel value in Gray */ inline uint8_t convert_pixel_rgb565_to_gray(uint16_t input) { int blue = (input & 0x1F00) >> 5; // blue int green = ((input & 0x7) << 5) | ((input & 0xE000) >> 11); // green int red = input & 0xF8; // red return convert_pixel_rgb888_to_gray(red, green, blue); } /** * @brief Crop a patch from image and resize and store to destination image. * If the cropping box is out of image, destination image will be padded with edge. * * The outer rectangle is the entire output image. * The inner rectangle is where the resized image will be stored. * In other world, this function could help you do padding while resize image. * ___________________________(dst_w)__________________ * | ___________________________ | * | |(x_start, y_start) | | * | | | | * | | | | * (dst_h)| | | | * | | | | * | | | | * | |___________________________|(x_end, y_end) | * |____________________________________________________| * * @tparam T suppot all integer types * @param dst_image pointer of destination(output) image * @param dst_width destination image width * @param dst_channel destination image channel number * @param dst_y_start start y of resized image in destination image * @param dst_y_end end y of resized image in destination image * @param dst_x_start start x of resized image in destination image * @param dst_x_end end x of resized image in destination image * @param src_image pointer of source image * @param src_height source image height * @param src_width source image width * @param src_channel source image channel * @param src_y_start start y of resized image in source image * @param src_y_end end y of resized image in source image * @param src_x_start start x of resized image in source image * @param src_x_end end x of resized image in source image * @param resize_type one of IMAGE_RESIZE_BILINEAR or IMAGE_RESIZE_MEAN or IMAGE_RESIZE_NEAREST * @param shift_left bit left shift number implemented on output */ template void crop_and_resize(T *dst_image, int dst_width, int dst_channel, int dst_y_start, int dst_y_end, int dst_x_start, int dst_x_end, uint16_t *src_image, int src_height, int src_width, int src_channel, int src_y_start, int src_y_end, int src_x_start, int src_x_end, resize_type_t resize_type = IMAGE_RESIZE_NEAREST, int shift_left = 0); /** * @brief Crop a patch from image and resize and store to destination image. * If the cropping box is out of image, destination image will be padded with edge. * * The outer rectangle is the entire output image. * The inner rectangle is where the resized image will be stored. * In other world, this function could help you do padding while resize image. * ___________________________(dst_w)__________________ * | ___________________________ | * | |(x_start, y_start) | | * | | | | * | | | | * (dst_h)| | | | * | | | | * | | | | * | |___________________________|(x_end, y_end) | * |____________________________________________________| * * @tparam T suppot all integer types * @param dst_image pointer of destination(output) image * @param dst_width destination image width * @param dst_channel destination image channel number * @param dst_y_start start y of resized image in destination image * @param dst_y_end end y of resized image in destination image * @param dst_x_start start x of resized image in destination image * @param dst_x_end end x of resized image in destination image * @param src_image pointer of source image * @param src_height source image height * @param src_width source image width * @param src_channel source image channel * @param src_y_start start y of resized image in source image * @param src_y_end end y of resized image in source image * @param src_x_start start x of resized image in source image * @param src_x_end end x of resized image in source image * @param resize_type one of IMAGE_RESIZE_BILINEAR or IMAGE_RESIZE_MEAN or IMAGE_RESIZE_NEAREST * @param shift_left bit left shift number implemented on output */ template void crop_and_resize(T *dst_image, int dst_width, int dst_channel, int dst_y_start, int dst_y_end, int dst_x_start, int dst_x_end, uint8_t *src_image, int src_height, int src_width, int src_channel, int src_y_start, int src_y_end, int src_x_start, int src_x_end, resize_type_t resize_type = IMAGE_RESIZE_NEAREST, int shift_left = 0); /** * @brief Draw a filled rectangle on RGB888 image. * * @param image pointer of input image * @param image_height height of input image * @param image_width width of input image * @param x1 left up corner x * @param y1 left up corner y * @param x2 right bottom corner x * @param y2 right bottom corner y * @param color 0x 00| 00| 00| 00 * reserved|channel 0|channel 1|channel 2 */ void draw_filled_rectangle(uint8_t *image, const uint32_t image_height, const uint32_t image_width, uint32_t x1, uint32_t y1, uint32_t x2, uint32_t y2, const uint32_t color = 0x00FF0000); /** * @brief Draw a filled rectangle on RGB565 image. * * @param image pointer of input image * @param image_height height of input image * @param image_width width of input image * @param x1 left up corner x * @param y1 left up corner y * @param x2 right bottom corner x * @param y2 right bottom corner y * @param color 0b 000| 00000| 00000| 000 * channel 1[2:0]|channel 0|channel 2|channel 1[5:3] */ void draw_filled_rectangle(uint16_t *image, const uint32_t image_height, const uint32_t image_width, uint32_t x1, uint32_t y1, uint32_t x2, uint32_t y2, const uint16_t color = 0b0001111100000000); /** * @brief Draw a point on RGB888 image. * * @param image pointer of input image * @param image_height height of input image * @param image_width width of input image * @param x point x * @param y point y * @param size size of point * @param color 0x 00| 00| 00| 00 * reserved|channel 0|channel 1|channel 2 */ void draw_point(uint8_t *image, const uint32_t image_height, const uint32_t image_width, const uint32_t x, const uint32_t y, const uint32_t size, const uint32_t color = 0x00FF0000); /** * @brief Draw a point on RGB565 image. * * @param image pointer of input image * @param image_height height of input image * @param image_width width of input image * @param x point x * @param y point y * @param size size of point * @param color 0b 000| 00000| 00000| 000 * channel 1[2:0]|channel 0|channel 2|channel 1[5:3] */ void draw_point(uint16_t *image, const uint32_t image_height, const uint32_t image_width, const uint32_t x, const uint32_t y, const uint32_t size, uint16_t color = 0b0001111100000000); /** * @brief Draw a hollow rectangle on RGB888 image. * * @param image pointer of input image * @param image_height height of input image * @param image_width width of input image * @param x1 left up corner x * @param y1 left up corner y * @param x2 right bottom corner x * @param y2 right bottom corner y * @param color 0x 00| 00| 00| 00 * reserved|channel 0|channel 1|channel 2 */ void draw_hollow_rectangle(uint8_t *image, const uint32_t image_height, const uint32_t image_width, uint32_t x1, uint32_t y1, uint32_t x2, uint32_t y2, uint32_t color = 0x00FF0000); /** * @brief Draw a hollow rectangle on RGB565 image. * * @param image pointer of input image * @param image_height height of input image * @param image_width width of input image * @param x1 left up corner x * @param y1 left up corner y * @param x2 right bottom corner x * @param y2 right bottom corner y * @param color 0b 000| 00000| 00000| 000 * channel 1[2:0]|channel 0|channel 2|channel 1[5:3] */ void draw_hollow_rectangle(uint16_t *image, const uint32_t image_height, const uint32_t image_width, uint32_t x1, uint32_t y1, uint32_t x2, uint32_t y2, const uint16_t color = 0b0001111100000000); /** * @brief Detect target moving by activated detection point number. Each cross in the figure below is a detection point. * Once abs(frame_1_detection_point[i] - frame_2_detection_point[i]) > threshold, this detection point is activated. * This function will return the number of activated detection point. * * __stride__________________________ * | | | | | * stride | | | | | * | | | | | * |________|________|________| | * | | | | | * | | | | | * | | | | | * |________|________|________| height * | | | | | * | | | | | * | | | | | * |________|________|________| | * | | | | | * | | | | | * | | | | | * |________|________|________|___|___ * | | * |__________width___________| * | | * * Time consumption: * Frame shape = (240, 240) * Both frame are in PSRAM * On ESP32-S3 with CPU 240MHz, QSPI 80MHz * * stride latency * 1 28316us * 2 8770us * 4 3622us * 8 1990us * 16 880us * 32 260us * * * In a application, outside this function, threshold of activated detection point number is needed. * Once activated detection point number > number_threshold, this two frame are judged target moved. * How to determine the number_threshold? * Let's assume that the minimize shape of target is (target_min_height, target_max_width). * Then, the number_threshold = [target_min_height / stride] * [target_max_width / stride] * ratio, * where ratio is in (0, 1), the smaller the ratio is, the more sensitive the detector is, the more false detected. * * * @param f1 one frame in RGB565 * @param f2 another frame in RGB565 * @param height height of frame * @param width width of frame * @param stride stride of detection point, the smaller the stride is, the more reliable the detector is. * @param threshold activation threshold of each detection point * @return activated detection point number */ uint32_t get_moving_point_number(uint16_t *f1, uint16_t *f2, const uint32_t height, const uint32_t width, const uint32_t stride, const uint32_t threshold = 5); /** * @brief Detect target moving by activated detection point number. Each cross in the figure below is a detection point. * Once abs(frame_1_detection_point[i] - frame_2_detection_point[i]) > threshold, this detection point is activated. * This function will return the number of activated detection point. * * __stride__________________________ * | | | | | * stride | | | | | * | | | | | * |________|________|________| | * | | | | | * | | | | | * | | | | | * |________|________|________| height * | | | | | * | | | | | * | | | | | * |________|________|________| | * | | | | | * | | | | | * | | | | | * |________|________|________|___|___ * | | * |__________width___________| * | | * * * In a application, outside this function, threshold of activated detection point number is needed. * Once activated detection point number > number_threshold, this two frame are judged target moved. * How to determine the number_threshold? * Let's assume that the minimize shape of target is (target_min_height, target_max_width). * Then, the number_threshold = [target_min_height / stride] * [target_max_width / stride] * ratio, * where ratio is in (0, 1), the smaller the ratio is, the more sensitive the detector is, the more false detected. * * * @param f1 one frame in RGB888 * @param f2 another frame in RGB888 * @param height height of frame * @param width width of frame * @param stride stride of detection point, the smaller the stride is, the more reliable the detector is. * @param threshold activation threshold of each detection point * @return activated detection point number */ uint32_t get_moving_point_number(uint8_t *f1, uint8_t *f2, const uint32_t height, const uint32_t width, const uint32_t stride, const uint32_t threshold = 5); /** * @brief Apply an affine transformation to an image. * * @tparam T * @param input the input image. * @param output the output image. * @param M_inv the inverse transformation matrix. */ template void warp_affine(dl::Tensor *input, dl::Tensor *output, dl::math::Matrix *M_inv); /** * @brief Apply an affine transformation to an image. * * @tparam T * @param input the pointer of the input image. * @param shape the shape of the input image. * @param output the output image. * @param M_inv the inverse transformation matrix. */ template void warp_affine(uint16_t *input, std::vector shape, dl::Tensor *output, dl::math::Matrix *M_inv); /** * @brief Get the otsu thresh object. * * @param image the gray image. * @return uint8_t the otsu thresh. */ uint8_t get_otsu_thresh(Tensor &image); /** * @brief Convert RGB image to gray image * * @param image input image * @param bgr true: the image is in BGR format * false: the image is in RGB format * @return Tensor* output image in gray format */ Tensor *rgb2gray(Tensor &image, bool bgr = false); /** * @brief Convert RGB image to LAB image * * @param image input image * @param bgr true: the image is in BGR format * false: the image is in RGB format * @param fast true: use the fast alogrithm， but the accuracy will be reduced * false: do not use the fast alogrithm * @return Tensor* output image in LAB foramt */ Tensor *rgb2lab(Tensor &image, bool bgr = false, bool fast = true); /** * @brief Convert RGB image to HSV image * * @param image input image * @param bgr true: the image is in BGR format * false: the image is in RGB format * @param fast true: use the fast alogrithm， but the accuracy will be reduced * false: do not use the fast alogrithm * @return Tensor* output image in HSV format */ Tensor *rgb2hsv(Tensor &image, bool bgr = false, bool fast = true); /** * @brief resize an image to the target shape. * * @param image the input image Tensor * @param target_shape the target shape of the resized image. * @param resize_type one of IMAGE_RESIZE_BILINEAR or IMAGE_RESIZE_MEAN or IMAGE_RESIZE_NEAREST * @return Tensor* the pointer of the resized image Tensor */ Tensor *resize_image(Tensor &image, std::vector target_shape, resize_type_t resize_type); /** * @brief resize an image to the target shape. * * @param image the input image Tensor * @param resized_image the resized image Tensor * @param resize_type one of IMAGE_RESIZE_BILINEAR or IMAGE_RESIZE_MEAN or IMAGE_RESIZE_NEAREST */ void resize_image(Tensor &image, Tensor &resized_image, resize_type_t resize_type); /** * @brief resize an image to the target shape with nearest method. * * @tparam T * @param image the pointer of the input image * @param input_shape the input shape of the image * @param target_shape the target shape of the resized image * @return T* the pointer of the resized image */ template T *resize_image_nearest(T *image, std::vector input_shape, std::vector target_shape); /** * @brief resize an image to the target shape with nearest method. * * @tparam T * @param image the pointer of the input image * @param input_shape the input shape of the image * @param resized_image the pointer of the resized image * @param target_shape the target shape of the resized image */ template void resize_image_nearest(T *image, std::vector input_shape, T *resized_image, std::vector target_shape); } // namespace image } // namespace dl