feedc0de/arduino-esp32
1
0
Fork 0
forked from espressif/arduino-esp32
Code Pull Requests Activity

v2.0.0 Add support for ESP32S2 and update ESP-IDF to 4.4 (#4996)

Browse Source 
This is very much still work in progress and much more will change before the final 2.0.0

Some APIs have changed. New libraries have been added. LittleFS included.

Co-authored-by: Seon Rozenblum <seonr@3sprockets.com>
Co-authored-by: Me No Dev <me-no-dev@users.noreply.github.com>
Co-authored-by: geeksville <kevinh@geeksville.com>
Co-authored-by: Mike Dunston <m_dunston@comcast.net>
Co-authored-by: Unexpected Maker <seon@unexpectedmaker.com>
Co-authored-by: Seon Rozenblum <seonr@3sprockets.com>
Co-authored-by: microDev <70126934+microDev1@users.noreply.github.com>
Co-authored-by: tobozo <tobozo@users.noreply.github.com>
Co-authored-by: bobobo1618 <bobobo1618@users.noreply.github.com>
Co-authored-by: lorol <lorolouis@gmail.com>
Co-authored-by: geeksville <kevinh@geeksville.com>
Co-authored-by: Limor "Ladyada" Fried <limor@ladyada.net>
Co-authored-by: Sweety <switi.mhaiske@espressif.com>
Co-authored-by: Loick MAHIEUX <loick111@gmail.com>
Co-authored-by: Larry Bernstone <lbernstone@gmail.com>
Co-authored-by: Valerii Koval <valeros@users.noreply.github.com>
Co-authored-by: 快乐的我531 <2302004040@qq.com>
Co-authored-by: chegewara <imperiaonline4@gmail.com>
Co-authored-by: Clemens Kirchgatterer <clemens@1541.org>
Co-authored-by: Aron Rubin <aronrubin@gmail.com>
Co-authored-by: Pete Lewis <601236+lewispg228@users.noreply.github.com>
This commit is contained in:
Me No Dev
2021-04-05 14:23:58 +03:00
committed by GitHub
parent 46d5afb17f
commit 5502879a5b
5209 changed files with 826360 additions and 322816 deletions
Download Patch File Download Diff File Expand all files Collapse all files

40
tools/sdk/esp32/include/esp-face/lib/include/cat_face_3.h Normal file
View File

@ -0,0 +1,40 @@
/*
* ESPRESSIF MIT License
*
* Copyright (c) 2018 <ESPRESSIF SYSTEMS (SHANGHAI) PTE LTD>
*
* Permission is hereby granted for use on ESPRESSIF SYSTEMS products only, in which case,
* it is free of charge, to any person_body obtaining a copy of this software and associated
* documentation files (the "Software"), to deal in the Software without restriction, including
* without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense,
* and/or sell copies of the Software, and to permit persons to whom the Software is furnished
* to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all copies or
* substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
* FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
* COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
* IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
* CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
*
*/
#pragma once
#ifdef __cplusplus
extern "C"
{
#endif
#include "dl_lib_matrix3d.h"
#include "dl_lib_matrix3dq.h"
#include "freertos/FreeRTOS.h"
#include "detection.h"
extern detection_model_t cat_face_3_model;
#ifdef __cplusplus
}
#endif

87
tools/sdk/esp32/include/esp-face/lib/include/detection.h Normal file
View File

@ -0,0 +1,87 @@
/*
* ESPRESSIF MIT License
*
* Copyright (c) 2018 <ESPRESSIF SYSTEMS (SHANGHAI) PTE LTD>
*
* Permission is hereby granted for use on ESPRESSIF SYSTEMS products only, in which case,
* it is free of charge, to any person obtaining a copy of this software and associated
* documentation files (the "Software"), to deal in the Software without restriction, including
* without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense,
* and/or sell copies of the Software, and to permit persons to whom the Software is furnished
* to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all copies or
* substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
* FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
* COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
* IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
* CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
*
*/
#pragma once
#ifdef __cplusplus
extern "C"
{
#endif
#include "dl_lib_matrix3d.h"
#include "dl_lib_matrix3dq.h"
#include "freertos/FreeRTOS.h"
typedef enum
{
Anchor_Point, /*<! Anchor point detection model*/
Anchor_Box /*<! Anchor box detection model */
} detection_model_type_t;
typedef struct
{
int **anchors_shape; /*<! Anchor shape of this stage */
int stride; /*<! Zoom in stride of this stage */
int boundary; /*<! Detection image low-limit of this stage */
int project_offset; /*<! Project offset of this stage */
} detection_stage_config_t;
typedef struct
{
dl_matrix3dq_t *score; /*<! score feature map of this stage*/
dl_matrix3dq_t *box_offset; /*<! box_offset feature map of this stage*/
dl_matrix3dq_t *landmark_offset; /*<! landmark_offset feature map of this stage */
} detection_stage_result_t;
typedef struct
{
int resized_height; /*<! The height after resized */
int resized_width; /*<! The width after resized */
fptp_t y_resize_scale; /*<! resized_height / input_height */
fptp_t x_resize_scale; /*<! resized_width / input_width */
qtp_t score_threshold; /*<! Score threshold of detection model */
fptp_t nms_threshold; /*<! NMS threshold of detection model */
bool with_landmark; /*<! Whether detection with landmark, true: with, false: without */
bool free_image; /*<! Whether free the resized image */
int enabled_top_k; /*<! The number of enabled stages */
} detection_model_config_t;
typedef struct
{
detection_stage_config_t *stage_config; /*<! Configuration of each stage */
int stage_number; /*<! The number of stages */
detection_model_type_t model_type; /*<! The type of detection model */
detection_model_config_t model_config; /*<! Configuration of detection model */
detection_stage_result_t *(*op)(dl_matrix3dq_t *, detection_model_config_t *); /*<! The function of detection inference */
void *(*get_boxes)(detection_stage_result_t *, detection_model_config_t *, detection_stage_config_t *, int); /*<! The function of how to get real boxes */
} detection_model_t;
/**
* @brief free 'detection_stage_result_t' type value
*
* @param value A 'detection_stage_result_t' type value
*/
void free_detection_stage_result(detection_stage_result_t value);
#ifdef __cplusplus
}
#endif

819
tools/sdk/esp32/include/esp-face/lib/include/dl_lib_matrix3d.h Normal file
View File

@ -0,0 +1,819 @@
#pragma once
#include <stdint.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
#include <assert.h>
#if CONFIG_SPIRAM_SUPPORT || CONFIG_ESP32_SPIRAM_SUPPORT
#include "freertos/FreeRTOS.h"
#define DL_SPIRAM_SUPPORT 1
#else
#define DL_SPIRAM_SUPPORT 0
#endif
#ifndef max
#define max(x, y) (((x) < (y)) ? (y) : (x))
#endif
#ifndef min
#define min(x, y) (((x) < (y)) ? (x) : (y))
#endif
typedef float fptp_t;
typedef uint8_t uc_t;
typedef enum
{
DL_SUCCESS = 0,
DL_FAIL = 1,
} dl_error_type;
typedef enum
{
PADDING_VALID = 0, /*!< Valid padding */
PADDING_SAME = 1, /*!< Same padding, from right to left, free input */
PADDING_SAME_DONT_FREE_INPUT = 2, /*!< Same padding, from right to left, do not free input */
PADDING_SAME_MXNET = 3, /*!< Same padding, from left to right */
} dl_padding_type;
typedef enum
{
DL_POOLING_MAX = 0, /*!< Max pooling */
DL_POOLING_AVG = 1, /*!< Average pooling */
} dl_pooling_type;
/*
* Matrix for 3d
* @Warning: the sequence of variables is fixed, cannot be modified, otherwise there will be errors in esp_dsp_dot_float
*/
typedef struct
{
int w; /*!< Width */
int h; /*!< Height */
int c; /*!< Channel */
int n; /*!< Number of filter, input and output must be 1 */
int stride; /*!< Step between lines */
fptp_t *item; /*!< Data */
} dl_matrix3d_t;
typedef struct
{
int w; /*!< Width */
int h; /*!< Height */
int c; /*!< Channel */
int n; /*!< Number of filter, input and output must be 1 */
int stride; /*!< Step between lines */
uc_t *item; /*!< Data */
} dl_matrix3du_t;
typedef enum
{
UPSAMPLE_NEAREST_NEIGHBOR = 0, /*!< Use nearest neighbor interpolation as the upsample method*/
UPSAMPLE_BILINEAR = 1, /*!< Use nearest bilinear interpolation as the upsample method*/
} dl_upsample_type;
typedef struct
{
int stride_x; /*!< Strides of width */
int stride_y; /*!< Strides of height */
dl_padding_type padding; /*!< Padding type */
} dl_matrix3d_mobilenet_config_t;
/*
* @brief Allocate a zero-initialized space. Must use 'dl_lib_free' to free the memory.
*
* @param cnt Count of units.
* @param size Size of unit.
* @param align Align of memory. If not required, set 0.
* @return Pointer of allocated memory. Null for failed.
*/
static void *dl_lib_calloc(int cnt, int size, int align)
{
int total_size = cnt * size + align + sizeof(void *);
void *res = malloc(total_size);
if (NULL == res)
{
#if DL_SPIRAM_SUPPORT
res = heap_caps_malloc(total_size, MALLOC_CAP_8BIT | MALLOC_CAP_SPIRAM);
}
if (NULL == res)
{
printf("Item psram alloc failed. Size: %d x %d\n", cnt, size);
#else
printf("Item alloc failed. Size: %d x %d, SPIRAM_FLAG: %d\n", cnt, size, DL_SPIRAM_SUPPORT);
#endif
return NULL;
}
bzero(res, total_size);
void **data = (void **)res + 1;
void **aligned;
if (align)
aligned = (void **)(((size_t)data + (align - 1)) & -align);
else
aligned = data;
aligned[-1] = res;
return (void *)aligned;
}
/**
* @brief Free the memory space allocated by 'dl_lib_calloc'
*
*/
static inline void dl_lib_free(void *d)
{
if (NULL == d)
return;
free(((void **)d)[-1]);
}
/*
* @brief Allocate a 3D matrix with float items, the access sequence is NHWC
*
* @param n Number of matrix3d, for filters it is out channels, for others it is 1
* @param w Width of matrix3d
* @param h Height of matrix3d
* @param c Channel of matrix3d
* @return 3d matrix
*/
static inline dl_matrix3d_t *dl_matrix3d_alloc(int n, int w, int h, int c)
{
dl_matrix3d_t *r = (dl_matrix3d_t *)dl_lib_calloc(1, sizeof(dl_matrix3d_t), 0);
if (NULL == r)
{
printf("internal r failed.\n");
return NULL;
}
fptp_t *items = (fptp_t *)dl_lib_calloc(n * w * h * c, sizeof(fptp_t), 0);
if (NULL == items)
{
printf("matrix3d item alloc failed.\n");
dl_lib_free(r);
return NULL;
}
r->w = w;
r->h = h;
r->c = c;
r->n = n;
r->stride = w * c;
r->item = items;
return r;
}
/*
* @brief Allocate a 3D matrix with 8-bits items, the access sequence is NHWC
*
* @param n Number of matrix3d, for filters it is out channels, for others it is 1
* @param w Width of matrix3d
* @param h Height of matrix3d
* @param c Channel of matrix3d
* @return 3d matrix
*/
static inline dl_matrix3du_t *dl_matrix3du_alloc(int n, int w, int h, int c)
{
dl_matrix3du_t *r = (dl_matrix3du_t *)dl_lib_calloc(1, sizeof(dl_matrix3du_t), 0);
if (NULL == r)
{
printf("internal r failed.\n");
return NULL;
}
uc_t *items = (uc_t *)dl_lib_calloc(n * w * h * c, sizeof(uc_t), 0);
if (NULL == items)
{
printf("matrix3du item alloc failed.\n");
dl_lib_free(r);
return NULL;
}
r->w = w;
r->h = h;
r->c = c;
r->n = n;
r->stride = w * c;
r->item = items;
return r;
}
/*
* @brief Free a matrix3d
*
* @param m matrix3d with float items
*/
static inline void dl_matrix3d_free(dl_matrix3d_t *m)
{
if (NULL == m)
return;
if (NULL == m->item)
{
dl_lib_free(m);
return;
}
dl_lib_free(m->item);
dl_lib_free(m);
}
/*
* @brief Free a matrix3d
*
* @param m matrix3d with 8-bits items
*/
static inline void dl_matrix3du_free(dl_matrix3du_t *m)
{
if (NULL == m)
return;
if (NULL == m->item)
{
dl_lib_free(m);
return;
}
dl_lib_free(m->item);
dl_lib_free(m);
}
/*
* @brief Dot product with a vector and matrix
*
* @param out Space to put the result
* @param in input vector
* @param f filter matrix
*/
void dl_matrix3dff_dot_product(dl_matrix3d_t *out, dl_matrix3d_t *in, dl_matrix3d_t *f);
/**
* @brief Do a softmax operation on a matrix3d
*
* @param in Input matrix3d
*/
void dl_matrix3d_softmax(dl_matrix3d_t *m);
/**
* @brief Copy a range of float items from an existing matrix to a preallocated matrix
*
* @param dst The destination slice matrix
* @param src The source matrix to slice
* @param x X-offset of the origin of the returned matrix within the sliced matrix
* @param y Y-offset of the origin of the returned matrix within the sliced matrix
* @param w Width of the resulting matrix
* @param h Height of the resulting matrix
*/
void dl_matrix3d_slice_copy(dl_matrix3d_t *dst,
dl_matrix3d_t *src,
int x,
int y,
int w,
int h);
/**
* @brief Copy a range of 8-bits items from an existing matrix to a preallocated matrix
*
* @param dst The destination slice matrix
* @param src The source matrix to slice
* @param x X-offset of the origin of the returned matrix within the sliced matrix
* @param y Y-offset of the origin of the returned matrix within the sliced matrix
* @param w Width of the resulting matrix
* @param h Height of the resulting matrix
*/
void dl_matrix3du_slice_copy(dl_matrix3du_t *dst,
dl_matrix3du_t *src,
int x,
int y,
int w,
int h);
/**
* @brief Transform a sliced matrix block from nhwc to nchw, the block needs to be memory continous.
*
* @param out The destination sliced matrix in nchw
* @param in The source sliced matrix in nhwc
*/
void dl_matrix3d_sliced_transform_nchw(dl_matrix3d_t *out,
dl_matrix3d_t *in);
/**
* @brief Do a general CNN layer pass, dimension is (number, width, height, channel)
*
* @param in Input matrix3d
* @param filter Weights of the neurons
* @param bias Bias for the CNN layer
* @param stride_x The step length of the convolution window in x(width) direction
* @param stride_y The step length of the convolution window in y(height) direction
* @param padding One of VALID or SAME
* @param mode Do convolution using C implement or xtensa implement, 0 or 1, with respect
* If ESP_PLATFORM is not defined, this value is not used. Default is 0
* @return dl_matrix3d_t* The result of CNN layer
*/
dl_matrix3d_t *dl_matrix3d_conv(dl_matrix3d_t *in,
dl_matrix3d_t *filter,
dl_matrix3d_t *bias,
int stride_x,
int stride_y,
int padding,
int mode);
/**
* @brief Do a global average pooling layer pass, dimension is (number, width, height, channel)
*
* @param in Input matrix3d
*
* @return The result of global average pooling layer
*/
dl_matrix3d_t *dl_matrix3d_global_pool(dl_matrix3d_t *in);
/**
* @brief Calculate pooling layer of a feature map
*
* @param in Input matrix, size (1, w, h, c)
* @param f_w Window width
* @param f_h Window height
* @param stride_x Stride in horizontal direction
* @param stride_y Stride in vertical direction
* @param padding Padding type: PADDING_VALID and PADDING_SAME
* @param pooling_type Pooling type: DL_POOLING_MAX and POOLING_AVG
* @return dl_matrix3d_t* Resulting matrix, size (1, w', h', c)
*/
dl_matrix3d_t *dl_matrix3d_pooling(dl_matrix3d_t *in,
int f_w,
int f_h,
int stride_x,
int stride_y,
dl_padding_type padding,
dl_pooling_type pooling_type);
/**
* @brief Do a batch normalization operation, update the input matrix3d: input = input * scale + offset
*
* @param m Input matrix3d
* @param scale scale matrix3d, scale = gamma/((moving_variance+sigma)^(1/2))
* @param Offset Offset matrix3d, offset = beta-(moving_mean*gamma/((moving_variance+sigma)^(1/2)))
*/
void dl_matrix3d_batch_normalize(dl_matrix3d_t *m,
dl_matrix3d_t *scale,
dl_matrix3d_t *offset);
/**
* @brief Add a pair of matrix3d item-by-item: res=in_1+in_2
*
* @param in_1 First Floating point input matrix3d
* @param in_2 Second Floating point input matrix3d
*
* @return dl_matrix3d_t* Added data
*/
dl_matrix3d_t *dl_matrix3d_add(dl_matrix3d_t *in_1, dl_matrix3d_t *in_2);
/**
* @brief Concatenate the channels of two matrix3ds into a new matrix3d
*
* @param in_1 First Floating point input matrix3d
* @param in_2 Second Floating point input matrix3d
*
* @return dl_matrix3d_t* A newly allocated matrix3d with as avlues in_1|in_2
*/
dl_matrix3d_t *dl_matrix3d_concat(dl_matrix3d_t *in_1, dl_matrix3d_t *in_2);
/**
* @brief Concatenate the channels of four matrix3ds into a new matrix3d
*
* @param in_1 First Floating point input matrix3d
* @param in_2 Second Floating point input matrix3d
* @param in_3 Third Floating point input matrix3d
* @param in_4 Fourth Floating point input matrix3d
*
* @return A newly allocated matrix3d with as avlues in_1|in_2|in_3|in_4
*/
dl_matrix3d_t *dl_matrix3d_concat_4(dl_matrix3d_t *in_1,
dl_matrix3d_t *in_2,
dl_matrix3d_t *in_3,
dl_matrix3d_t *in_4);
/**
* @brief Concatenate the channels of eight matrix3ds into a new matrix3d
*
* @param in_1 First Floating point input matrix3d
* @param in_2 Second Floating point input matrix3d
* @param in_3 Third Floating point input matrix3d
* @param in_4 Fourth Floating point input matrix3d
* @param in_5 Fifth Floating point input matrix3d
* @param in_6 Sixth Floating point input matrix3d
* @param in_7 Seventh Floating point input matrix3d
* @param in_8 eighth Floating point input matrix3d
*
* @return A newly allocated matrix3d with as avlues in_1|in_2|in_3|in_4|in_5|in_6|in_7|in_8
*/
dl_matrix3d_t *dl_matrix3d_concat_8(dl_matrix3d_t *in_1,
dl_matrix3d_t *in_2,
dl_matrix3d_t *in_3,
dl_matrix3d_t *in_4,
dl_matrix3d_t *in_5,
dl_matrix3d_t *in_6,
dl_matrix3d_t *in_7,
dl_matrix3d_t *in_8);
/**
* @brief Do a mobilefacenet block forward, dimension is (number, width, height, channel)
*
* @param in Input matrix3d
* @param pw Weights of the pointwise conv layer
* @param pw_bn_scale The scale params of the batch_normalize layer after the pointwise conv layer
* @param pw_bn_offset The offset params of the batch_normalize layer after the pointwise conv layer
* @param dw Weights of the depthwise conv layer
* @param dw_bn_scale The scale params of the batch_normalize layer after the depthwise conv layer
* @param dw_bn_offset The offset params of the batch_normalize layer after the depthwise conv layer
* @param pw_linear Weights of the pointwise linear conv layer
* @param pw_linear_bn_scale The scale params of the batch_normalize layer after the pointwise linear conv layer
* @param pw_linear_bn_offset The offset params of the batch_normalize layer after the pointwise linear conv layer
* @param stride_x The step length of the convolution window in x(width) direction
* @param stride_y The step length of the convolution window in y(height) direction
* @param padding One of VALID or SAME
* @param mode Do convolution using C implement or xtensa implement, 0 or 1, with respect
* If ESP_PLATFORM is not defined, this value is not used. Default is 0
* @return The result of a mobilefacenet block
*/
dl_matrix3d_t *dl_matrix3d_mobilefaceblock(dl_matrix3d_t *in,
dl_matrix3d_t *pw,
dl_matrix3d_t *pw_bn_scale,
dl_matrix3d_t *pw_bn_offset,
dl_matrix3d_t *dw,
dl_matrix3d_t *dw_bn_scale,
dl_matrix3d_t *dw_bn_offset,
dl_matrix3d_t *pw_linear,
dl_matrix3d_t *pw_linear_bn_scale,
dl_matrix3d_t *pw_linear_bn_offset,
int stride_x,
int stride_y,
int padding,
int mode,
int shortcut);
/**
* @brief Do a mobilefacenet block forward with 1x1 split conv, dimension is (number, width, height, channel)
*
* @param in Input matrix3d
* @param pw_1 Weights of the pointwise conv layer 1
* @param pw_2 Weights of the pointwise conv layer 2
* @param pw_bn_scale The scale params of the batch_normalize layer after the pointwise conv layer
* @param pw_bn_offset The offset params of the batch_normalize layer after the pointwise conv layer
* @param dw Weights of the depthwise conv layer
* @param dw_bn_scale The scale params of the batch_normalize layer after the depthwise conv layer
* @param dw_bn_offset The offset params of the batch_normalize layer after the depthwise conv layer
* @param pw_linear_1 Weights of the pointwise linear conv layer 1
* @param pw_linear_2 Weights of the pointwise linear conv layer 2
* @param pw_linear_bn_scale The scale params of the batch_normalize layer after the pointwise linear conv layer
* @param pw_linear_bn_offset The offset params of the batch_normalize layer after the pointwise linear conv layer
* @param stride_x The step length of the convolution window in x(width) direction
* @param stride_y The step length of the convolution window in y(height) direction
* @param padding One of VALID or SAME
* @param mode Do convolution using C implement or xtensa implement, 0 or 1, with respect
* If ESP_PLATFORM is not defined, this value is not used. Default is 0
* @return The result of a mobilefacenet block
*/
dl_matrix3d_t *dl_matrix3d_mobilefaceblock_split(dl_matrix3d_t *in,
dl_matrix3d_t *pw_1,
dl_matrix3d_t *pw_2,
dl_matrix3d_t *pw_bn_scale,
dl_matrix3d_t *pw_bn_offset,
dl_matrix3d_t *dw,
dl_matrix3d_t *dw_bn_scale,
dl_matrix3d_t *dw_bn_offset,
dl_matrix3d_t *pw_linear_1,
dl_matrix3d_t *pw_linear_2,
dl_matrix3d_t *pw_linear_bn_scale,
dl_matrix3d_t *pw_linear_bn_offset,
int stride_x,
int stride_y,
int padding,
int mode,
int shortcut);
/**
* @brief Initialize the matrix3d feature map to bias
*
* @param out The matrix3d feature map needs to be initialized
* @param bias The bias of a convlotion operation
*/
void dl_matrix3d_init_bias(dl_matrix3d_t *out, dl_matrix3d_t *bias);
/**
* @brief Do a elementwise multiplication of two matrix3ds
*
* @param out Preallocated matrix3d, size (n, w, h, c)
* @param in1 Input matrix 1, size (n, w, h, c)
* @param in2 Input matrix 2, size (n, w, h, c)
*/
void dl_matrix3d_multiply(dl_matrix3d_t *out, dl_matrix3d_t *in1, dl_matrix3d_t *in2);
//
// Activation
//
/**
* @brief Do a standard relu operation, update the input matrix3d
*
* @param m Floating point input matrix3d
*/
void dl_matrix3d_relu(dl_matrix3d_t *m);
/**
* @brief Do a relu (Rectifier Linear Unit) operation, update the input matrix3d
*
* @param in Floating point input matrix3d
* @param clip If value is higher than this, it will be clipped to this value
*/
void dl_matrix3d_relu_clip(dl_matrix3d_t *m, fptp_t clip);
/**
* @brief Do a Prelu (Rectifier Linear Unit) operation, update the input matrix3d
*
* @param in Floating point input matrix3d
* @param alpha If value is less than zero, it will be updated by multiplying this factor
*/
void dl_matrix3d_p_relu(dl_matrix3d_t *in, dl_matrix3d_t *alpha);
/**
* @brief Do a leaky relu (Rectifier Linear Unit) operation, update the input matrix3d
*
* @param in Floating point input matrix3d
* @param alpha If value is less than zero, it will be updated by multiplying this factor
*/
void dl_matrix3d_leaky_relu(dl_matrix3d_t *m, fptp_t alpha);
//
// Conv 1x1
//
/**
* @brief Do 1x1 convolution with a matrix3d
*
* @param out Preallocated matrix3d, size (1, w, h, n)
* @param in Input matrix, size (1, w, h, c)
* @param filter 1x1 filter, size (n, 1, 1, c)
*/
void dl_matrix3dff_conv_1x1(dl_matrix3d_t *out,
dl_matrix3d_t *in,
dl_matrix3d_t *filter);
/**
* @brief Do 1x1 convolution with a matrix3d, with bias adding
*
* @param out Preallocated matrix3d, size (1, w, h, n)
* @param in Input matrix, size (1, w, h, c)
* @param filter 1x1 filter, size (n, 1, 1, c)
* @param bias Bias, size (1, 1, 1, n)
*/
void dl_matrix3dff_conv_1x1_with_bias(dl_matrix3d_t *out,
dl_matrix3d_t *in,
dl_matrix3d_t *filter,
dl_matrix3d_t *bias);
/**
* @brief Do 1x1 convolution with an 8-bit fixed point matrix
*
* @param out Preallocated matrix3d, size (1, w, h, n)
* @param in Input matrix, size (1, w, h, c)
* @param filter 1x1 filter, size (n, 1, 1, c)
*/
void dl_matrix3duf_conv_1x1(dl_matrix3d_t *out,
dl_matrix3du_t *in,
dl_matrix3d_t *filter);
/**
* @brief Do 1x1 convolution with an 8-bit fixed point matrix, with bias adding
*
* @param out Preallocated matrix3d, size (1, w, h, n)
* @param in Input matrix, size (1, w, h, c)
* @param filter 1x1 filter, size (n, 1, 1, c)
* @param bias Bias, size (1, 1, 1, n)
*/
void dl_matrix3duf_conv_1x1_with_bias(dl_matrix3d_t *out,
dl_matrix3du_t *in,
dl_matrix3d_t *filter,
dl_matrix3d_t *bias);
//
// Conv 3x3
//
/**
* @brief Do 3x3 convolution with a matrix3d, without padding
*
* @param out Preallocated matrix3d, size (1, w, h, n)
* @param in Input matrix, size (1, w, h, c)
* @param f 3x3 filter, size (n, 3, 3, c)
* @param step_x Stride of width
* @param step_y Stride of height
*/
void dl_matrix3dff_conv_3x3_op(dl_matrix3d_t *out,
dl_matrix3d_t *in,
dl_matrix3d_t *f,
int step_x,
int step_y);
/**
* @brief Do 3x3 convolution with a matrix3d, with bias adding
*
* @param input Input matrix, size (1, w, h, c)
* @param filter 3x3 filter, size (n, 3, 3, c)
* @param bias Bias, size (1, 1, 1, n)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type
* @return dl_matrix3d_t* Resulting matrix3d
*/
dl_matrix3d_t *dl_matrix3dff_conv_3x3(dl_matrix3d_t *in,
dl_matrix3d_t *filter,
dl_matrix3d_t *bias,
int stride_x,
int stride_y,
dl_padding_type padding);
//
// Conv Common
//
/**
* @brief Do a general convolution layer pass with an 8-bit fixed point matrix, size is (number, width, height, channel)
*
* @param in Input image
* @param filter Weights of the neurons
* @param bias Bias for the CNN layer
* @param stride_x The step length of the convolution window in x(width) direction
* @param stride_y The step length of the convolution window in y(height) direction
* @param padding Padding type
* @return dl_matrix3d_t* Resulting matrix3d
*/
dl_matrix3d_t *dl_matrix3duf_conv_common(dl_matrix3du_t *in,
dl_matrix3d_t *filter,
dl_matrix3d_t *bias,
int stride_x,
int stride_y,
dl_padding_type padding);
/**
* @brief Do a general convolution layer pass, size is (number, width, height, channel)
*
* @param in Input image
* @param filter Weights of the neurons
* @param bias Bias for the CNN layer
* @param stride_x The step length of the convolution window in x(width) direction
* @param stride_y The step length of the convolution window in y(height) direction
* @param padding Padding type
* @return dl_matrix3d_t* Resulting matrix3d
*/
dl_matrix3d_t *dl_matrix3dff_conv_common(dl_matrix3d_t *in,
dl_matrix3d_t *filter,
dl_matrix3d_t *bias,
int stride_x,
int stride_y,
dl_padding_type padding);
//
// Depthwise 3x3
//
/**
* @brief Do 3x3 depthwise convolution with a float matrix3d
*
* @param in Input matrix, size (1, w, h, c)
* @param filter 3x3 filter, size (1, 3, 3, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type, 0: valid, 1: same
* @return dl_matrix3d_t* Resulting float matrix3d
*/
dl_matrix3d_t *dl_matrix3dff_depthwise_conv_3x3(dl_matrix3d_t *in,
dl_matrix3d_t *filter,
int stride_x,
int stride_y,
int padding);
/**
* @brief Do 3x3 depthwise convolution with a 8-bit fixed point matrix
*
* @param in Input matrix, size (1, w, h, c)
* @param filter 3x3 filter, size (1, 3, 3, c)
* @param stride_x Stride of width
* @param stride_y Stride of height
* @param padding Padding type, 0: valid, 1: same
* @return dl_matrix3d_t* Resulting float matrix3d
*/
dl_matrix3d_t *dl_matrix3duf_depthwise_conv_3x3(dl_matrix3du_t *in,
dl_matrix3d_t *filter,
int stride_x,
int stride_y,
int padding);
/**
* @brief Do 3x3 depthwise convolution with a float matrix3d, without padding
*
* @param out Preallocated matrix3d, size (1, w, h, n)
* @param in Input matrix, size (1, w, h, c)
* @param f 3x3 filter, size (1, 3, 3, c)
* @param step_x Stride of width
* @param step_y Stride of height
*/
void dl_matrix3dff_depthwise_conv_3x3_op(dl_matrix3d_t *out,
dl_matrix3d_t *in,
dl_matrix3d_t *f,
int step_x,
int step_y);
//
// Depthwise Common
//
/**
* @brief Do a depthwise CNN layer pass, dimension is (number, width, height, channel)
*
* @param in Input matrix3d
* @param filter Weights of the neurons
* @param stride_x The step length of the convolution window in x(width) direction
* @param stride_y The step length of the convolution window in y(height) direction
* @param padding One of VALID or SAME
* @param mode Do convolution using C implement or xtensa implement, 0 or 1, with respect
* If ESP_PLATFORM is not defined, this value is not used. Default is 0
* @return The result of depthwise CNN layer
*/
dl_matrix3d_t *dl_matrix3dff_depthwise_conv_common(dl_matrix3d_t *in,
dl_matrix3d_t *filter,
int stride_x,
int stride_y,
dl_padding_type padding);
//
// FC
//
/**
* @brief Do a general fully connected layer pass, dimension is (number, width, height, channel)
*
* @param in Input matrix3d, size is (1, w, 1, 1)
* @param filter Weights of the neurons, size is (1, w, h, 1)
* @param bias Bias for the fc layer, size is (1, 1, 1, h)
* @return The result of fc layer, size is (1, 1, 1, h)
*/
void dl_matrix3dff_fc(dl_matrix3d_t *out,
dl_matrix3d_t *in,
dl_matrix3d_t *filter);
/**
* @brief Do fully connected layer forward, with bias adding
*
* @param out Preallocated resulting matrix, size (1, 1, 1, h)
* @param in Input matrix, size (1, 1, 1, w)
* @param filter Filter matrix, size (1, w, h, 1)
* @param bias Bias matrix, size (1, 1, 1, h)
*/
void dl_matrix3dff_fc_with_bias(dl_matrix3d_t *out,
dl_matrix3d_t *in,
dl_matrix3d_t *filter,
dl_matrix3d_t *bias);
//
// Mobilenet
//
/**
* @brief Do a mobilenet block forward, dimension is (number, width, height, channel)
*
* @param in Input matrix3d
* @param filter Weights of the neurons
* @param stride_x The step length of the convolution window in x(width) direction
* @param stride_y The step length of the convolution window in y(height) direction
* @param padding One of VALID or SAME
* @param mode Do convolution using C implement or xtensa implement, 0 or 1, with respect
* If ESP_PLATFORM is not defined, this value is not used. Default is 0
* @return The result of depthwise CNN layer
*/
dl_matrix3d_t *dl_matrix3dff_mobilenet(dl_matrix3d_t *in,
dl_matrix3d_t *dilate_filter,
dl_matrix3d_t *dilate_prelu,
dl_matrix3d_t *depthwise_filter,
dl_matrix3d_t *depthwise_prelu,
dl_matrix3d_t *compress_filter,
dl_matrix3d_t *bias,
dl_matrix3d_mobilenet_config_t config);
/**
* @brief Do a mobilenet block forward, dimension is (number, width, height, channel)
*
* @param in Input matrix3du
* @param filter Weights of the neurons
* @param stride_x The step length of the convolution window in x(width) direction
* @param stride_y The step length of the convolution window in y(height) direction
* @param padding One of VALID or SAME
* @param mode Do convolution using C implement or xtensa implement, 0 or 1, with respect
* If ESP_PLATFORM is not defined, this value is not used. Default is 0
* @return The result of depthwise CNN layer
*/
dl_matrix3d_t *dl_matrix3duf_mobilenet(dl_matrix3du_t *in,
dl_matrix3d_t *dilate_filter,
dl_matrix3d_t *dilate_prelu,
dl_matrix3d_t *depthwise_filter,
dl_matrix3d_t *depthwise_prelu,
dl_matrix3d_t *compress_filter,
dl_matrix3d_t *bias,
dl_matrix3d_mobilenet_config_t config);

1441
tools/sdk/esp32/include/esp-face/lib/include/dl_lib_matrix3dq.h Normal file
View File

File diff suppressed because it is too large Load Diff

43
tools/sdk/esp32/include/esp-face/lib/include/frmn.h Normal file
View File

@ -0,0 +1,43 @@
#pragma once
#if __cplusplus
extern "C"
{
#endif
#include "dl_lib_matrix3d.h"
#include "dl_lib_matrix3dq.h"
/**
* @brief Forward the face recognition process with frmn model. Calculate in float.
*
* @param in Image matrix, rgb888 format, size is 56x56, normalized
* @return dl_matrix3d_t* Face ID feature vector, size is 512
*/
dl_matrix3d_t *frmn(dl_matrix3d_t *in);
/**@{*/
/**
* @brief Forward the face recognition process with specified model. Calculate in quantization.
*
* @param in Image matrix, rgb888 format, size is 56x56, normalized
* @param mode 0: C implement; 1: handwrite xtensa instruction implement
* @return Face ID feature vector, size is 512
*/
dl_matrix3dq_t *frmn_q(dl_matrix3dq_t *in, dl_conv_mode mode);
dl_matrix3dq_t *frmn2p_q(dl_matrix3dq_t *in, dl_conv_mode mode);
dl_matrix3dq_t *mfn56_42m_q(dl_matrix3dq_t *in, dl_conv_mode mode);
dl_matrix3dq_t *mfn56_72m_q(dl_matrix3dq_t *in, dl_conv_mode mode);
dl_matrix3dq_t *mfn56_112m_q(dl_matrix3dq_t *in, dl_conv_mode mode);
dl_matrix3dq_t *mfn56_156m_q(dl_matrix3dq_t *in, dl_conv_mode mode);
/**@}*/
#if __cplusplus
}
#endif

66
tools/sdk/esp32/include/esp-face/lib/include/hd_model.h Normal file
View File

@ -0,0 +1,66 @@
#pragma once
#if __cplusplus
extern "C"
{
#endif
#include "dl_lib_matrix3d.h"
#include "dl_lib_matrix3dq.h"
typedef struct
{
int num; /*!< The total number of the boxes */
dl_matrix3d_t *cls; /*!< The class feature map corresponding to the box. size: (height, width, anchor_num, 1) */
dl_matrix3d_t *score; /*!< The confidence score feature map of the class corresponding to the box. size: (height, width, anchor_num, 1) */
dl_matrix3d_t *boxes; /*!< (x, y, w, h) of the boxes. x and y are the center coordinates. size:(height, width, anchor_num, 4) */
} detection_result_t;
/**
* @brief Forward the hand detection process with hd_nano1 model. Calculate in quantization.
*
* @param in A normalized image matrix in rgb888 format, its width and height must be integer multiples of 16.
* @param mode 0: C implement; 1: handwrite xtensa instruction implement
* @return detection_result_t** Detection results
*/
detection_result_t **hd_nano1_q(dl_matrix3dq_t *in, dl_conv_mode mode);
/**
* @brief Forward the hand detection process with hd_lite1 model. Calculate in quantization.
*
* @param in A normalized image matrix in rgb888 format, its width and height must be integer multiples of 32.
* @param mode 0: C implement; 1: handwrite xtensa instruction implement.
* @return detection_result_t** Detection results.
*/
detection_result_t **hd_lite1_q(dl_matrix3dq_t *in, dl_conv_mode mode);
/**
* @brief Free the single detection result.
*
* @param m The single detection result.
*/
void detection_result_free(detection_result_t *m);
/**
* @brief Free the detection result group from different feature map.
*
* @param m The detection result group
* @param length The number of the detection results
*/
void detection_results_free(detection_result_t **m, int length);
/**
* @brief Test the result of hand detection model.
*
*/
void hd_test();
/**
* @brief Test the forward time of hand detection model.
*
*/
void hd_time_test();
#if __cplusplus
}
#endif

43
tools/sdk/esp32/include/esp-face/lib/include/hp_model.h Normal file
View File

@ -0,0 +1,43 @@
#pragma once
#if __cplusplus
extern "C"
{
#endif
#include "dl_lib_matrix3d.h"
#include "dl_lib_matrix3dq.h"
/**
* @brief Forward the hand pose estimation process with hp_nano1_ls16 model. Calculate in quantization.
*
* @param in A normalized image matrix in rgb888 format, its size is (1, 128, 128, 3).
* @param mode 0: C implement; 1: handwrite xtensa instruction implement
* @return dl_matrix3d_t* The resulting hand joint point coordinates, the size is (1, 1, 21, 2)
*/
dl_matrix3d_t *hp_nano1_ls16_q(dl_matrix3dq_t *in, dl_conv_mode mode);
/**
* @brief Forward the hand pose estimation process with hp_lite1 model. Calculate in quantization.
*
* @param in A normalized image matrix in rgb888 format, its size is (1, 128, 128, 3).
* @param mode 0: C implement; 1: handwrite xtensa instruction implement
* @return dl_matrix3d_t* The resulting hand joint point coordinates, the size is (1, 1, 21, 2)
*/
dl_matrix3d_t *hp_lite1_q(dl_matrix3dq_t *in, dl_conv_mode mode);
/**
* @brief Test the result of hand pose estimation model.
*
*/
void hp_test();
/**
* @brief Test the forward time of hand pose estimation model.
*
*/
void hp_time_test();
#if __cplusplus
}
#endif

91
tools/sdk/esp32/include/esp-face/lib/include/lssh.h Normal file
View File

@ -0,0 +1,91 @@
/*
* ESPRESSIF MIT License
*
* Copyright (c) 2018 <ESPRESSIF SYSTEMS (SHANGHAI) PTE LTD>
*
* Permission is hereby granted for use on ESPRESSIF SYSTEMS products only, in which case,
* it is free of charge, to any person obtaining a copy of this software and associated
* documentation files (the "Software"), to deal in the Software without restriction, including
* without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense,
* and/or sell copies of the Software, and to permit persons to whom the Software is furnished
* to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all copies or
* substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
* FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
* COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
* IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
* CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
*
*/
#pragma once
#ifdef __cplusplus
extern "C"
{
#endif
#include "dl_lib_matrix3d.h"
#include "dl_lib_matrix3dq.h"
#include "freertos/FreeRTOS.h"
typedef struct
{
int resized_height;
int resized_width;
fptp_t y_resize_scale;
fptp_t x_resize_scale;
int enabled_top_k;
fptp_t score_threshold;
fptp_t nms_threshold;
dl_conv_mode mode;
} lssh_config_t;
typedef struct
{
int *anchor_size;
int stride;
int boundary;
} lssh_module_config_t;
typedef struct
{
lssh_module_config_t *module_config;
int number;
} lssh_modules_config_t;
typedef struct
{
dl_matrix3d_t *category;
dl_matrix3d_t *box_offset;
dl_matrix3d_t *landmark_offset;
} lssh_module_result_t;
/**
* @brief
*
* @param value
*/
void lssh_module_result_free(lssh_module_result_t value);
/**
* @brief
*
* @param values
* @param length
*/
void lssh_module_results_free(lssh_module_result_t *values, int length);
/////////////////////////
//////sparse_mn_5_q//////
/////////////////////////
extern lssh_modules_config_t sparse_mn_5_modules_config;
lssh_module_result_t *sparse_mn_5_q_without_landmark(dl_matrix3du_t *image, bool free_image, int enabled_top_k, dl_conv_mode mode);
lssh_module_result_t *sparse_mn_5_q_with_landmark(dl_matrix3du_t *image, bool free_image, int enabled_top_k, dl_conv_mode mode);
#ifdef __cplusplus
}
#endif

142
tools/sdk/esp32/include/esp-face/lib/include/mtmn.h Normal file
View File

@ -0,0 +1,142 @@
/*
* ESPRESSIF MIT License
*
* Copyright (c) 2018 <ESPRESSIF SYSTEMS (SHANGHAI) PTE LTD>
*
* Permission is hereby granted for use on ESPRESSIF SYSTEMS products only, in which case,
* it is free of charge, to any person obtaining a copy of this software and associated
* documentation files (the "Software"), to deal in the Software without restriction, including
* without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense,
* and/or sell copies of the Software, and to permit persons to whom the Software is furnished
* to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in all copies or
* substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
* FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
* COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
* IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
* CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
*
*/
#pragma once
#ifdef __cplusplus
extern "C"
{
#endif
#include "dl_lib_matrix3d.h"
#include "dl_lib_matrix3dq.h"
/**
* Detection results with MTMN.
*
*/
typedef struct
{
dl_matrix3d_t *category; /*!< Classification result after softmax, channel is 2 */
dl_matrix3d_t *offset; /*!< Bounding box offset of 2 points: top-left and bottom-right, channel is 4 */
dl_matrix3d_t *landmark; /*!< Offsets of 5 landmarks:
* - Left eye
* - Mouth leftside
* - Nose
* - Right eye
* - Mouth rightside
*
* channel is 10
* */
} mtmn_net_t;
/**
* @brief Free a mtmn_net_t
*
* @param p A mtmn_net_t pointer
*
*/
void mtmn_net_t_free(mtmn_net_t *p);
/**
* @brief Forward the pnet process, coarse detection. Calculate in float.
*
* @param in Image matrix, rgb888 format, size is 320x240
* @return Scores for every pixel, and box offset with respect.
*/
mtmn_net_t *pnet_lite_f(dl_matrix3du_t *in);
/**
* @brief Forward the rnet process, fine determine the boxes from pnet. Calculate in float.
*
* @param in Image matrix, rgb888 format
* @param threshold Score threshold to detect human face
* @return Scores for every box, and box offset with respect.
*/
mtmn_net_t *rnet_lite_f_with_score_verify(dl_matrix3du_t *in, float threshold);
/**
* @brief Forward the onet process, fine determine the boxes from rnet. Calculate in float.
*
* @param in Image matrix, rgb888 format
* @param threshold Score threshold to detect human face
* @return Scores for every box, box offset, and landmark with respect.
*/
mtmn_net_t *onet_lite_f_with_score_verify(dl_matrix3du_t *in, float threshold);
/**
* @brief Forward the pnet process, coarse detection. Calculate in quantization.
*
* @param in Image matrix, rgb888 format, size is 320x240
* @return Scores for every pixel, and box offset with respect.
*/
mtmn_net_t *pnet_lite_q(dl_matrix3du_t *in, dl_conv_mode mode);
/**
* @brief Forward the rnet process, fine determine the boxes from pnet. Calculate in quantization.
*
* @param in Image matrix, rgb888 format
* @param threshold Score threshold to detect human face
* @return Scores for every box, and box offset with respect.
*/
mtmn_net_t *rnet_lite_q_with_score_verify(dl_matrix3du_t *in, float threshold, dl_conv_mode mode);
/**
* @brief Forward the onet process, fine determine the boxes from rnet. Calculate in quantization.
*
* @param in Image matrix, rgb888 format
* @param threshold Score threshold to detect human face
* @return Scores for every box, box offset, and landmark with respect.
*/
mtmn_net_t *onet_lite_q_with_score_verify(dl_matrix3du_t *in, float threshold, dl_conv_mode mode);
/**
* @brief Forward the pnet process, coarse detection. Calculate in quantization.
*
* @param in Image matrix, rgb888 format, size is 320x240
* @return Scores for every pixel, and box offset with respect.
*/
mtmn_net_t *pnet_heavy_q(dl_matrix3du_t *in, dl_conv_mode mode);
/**
* @brief Forward the rnet process, fine determine the boxes from pnet. Calculate in quantization.
*
* @param in Image matrix, rgb888 format
* @param threshold Score threshold to detect human face
* @return Scores for every box, and box offset with respect.
*/
mtmn_net_t *rnet_heavy_q_with_score_verify(dl_matrix3du_t *in, float threshold, dl_conv_mode mode);
/**
* @brief Forward the onet process, fine determine the boxes from rnet. Calculate in quantization.
*
* @param in Image matrix, rgb888 format
* @param threshold Score threshold to detect human face
* @return Scores for every box, box offset, and landmark with respect.
*/
mtmn_net_t *onet_heavy_q_with_score_verify(dl_matrix3du_t *in, float threshold, dl_conv_mode mode);
#ifdef __cplusplus
}
#endif