// Copyright 2015-2016 Espressif Systems (Shanghai) PTE LTD
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "esp_http_server.h"
#include "esp_timer.h"
#include "esp_camera.h"
#include "img_converters.h"
#include "fb_gfx.h"
#include "esp32-hal-ledc.h"
#include "sdkconfig.h"
#include "camera_index.h"
#if defined(ARDUINO_ARCH_ESP32) && defined(CONFIG_ARDUHAL_ESP_LOG)
#include "esp32-hal-log.h"
#endif
// Face Detection will not work on boards without (or with disabled) PSRAM
#ifdef BOARD_HAS_PSRAM
// Face Recognition takes upward from 15 seconds per frame on chips other than ESP32S3
// Makes no sense to have it enabled for them
#if CONFIG_IDF_TARGET_ESP32S3
#define CONFIG_ESP_FACE_RECOGNITION_ENABLED 1
#define CONFIG_ESP_FACE_DETECT_ENABLED 1
#else
#define CONFIG_ESP_FACE_RECOGNITION_ENABLED 0
#define CONFIG_ESP_FACE_DETECT_ENABLED 0
#endif
#else
#define CONFIG_ESP_FACE_DETECT_ENABLED 0
#define CONFIG_ESP_FACE_RECOGNITION_ENABLED 0
#endif
#if CONFIG_ESP_FACE_DETECT_ENABLED
#include <vector>
#include "human_face_detect_msr01.hpp"
#include "human_face_detect_mnp01.hpp"
#define TWO_STAGE 1 /*<! 1: detect by two-stage which is more accurate but slower(with keypoints). */
/*<! 0: detect by one-stage which is less accurate but faster(without keypoints). */
#if CONFIG_ESP_FACE_RECOGNITION_ENABLED
#pragma GCC diagnostic ignored "-Wformat"
#pragma GCC diagnostic ignored "-Wstrict-aliasing"
#include "face_recognition_tool.hpp"
#include "face_recognition_112_v1_s16.hpp"
#include "face_recognition_112_v1_s8.hpp"
#pragma GCC diagnostic error "-Wformat"
#pragma GCC diagnostic warning "-Wstrict-aliasing"
#define QUANT_TYPE 0 //if set to 1 => very large firmware, very slow, reboots when streaming...
#define FACE_ID_SAVE_NUMBER 7
#endif
#define FACE_COLOR_WHITE 0x00FFFFFF
#define FACE_COLOR_BLACK 0x00000000
#define FACE_COLOR_RED 0x000000FF
#define FACE_COLOR_GREEN 0x0000FF00
#define FACE_COLOR_BLUE 0x00FF0000
#define FACE_COLOR_YELLOW (FACE_COLOR_RED | FACE_COLOR_GREEN)
#define FACE_COLOR_CYAN (FACE_COLOR_BLUE | FACE_COLOR_GREEN)
#define FACE_COLOR_PURPLE (FACE_COLOR_BLUE | FACE_COLOR_RED)
#endif
// Enable LED FLASH setting
#define CONFIG_LED_ILLUMINATOR_ENABLED 1
// LED FLASH setup
#if CONFIG_LED_ILLUMINATOR_ENABLED
#define LED_LEDC_GPIO 22 //configure LED pin
#define CONFIG_LED_MAX_INTENSITY 255
int led_duty = 0;
bool isStreaming = false;
#endif
typedef struct {
httpd_req_t *req;
size_t len;
} jpg_chunking_t;
#define PART_BOUNDARY "123456789000000000000987654321"
static const char *_STREAM_CONTENT_TYPE = "multipart/x-mixed-replace;boundary=" PART_BOUNDARY;
static const char *_STREAM_BOUNDARY = "\r\n--" PART_BOUNDARY "\r\n";
static const char *_STREAM_PART = "Content-Type: image/jpeg\r\nContent-Length: %u\r\nX-Timestamp: %d.%06d\r\n\r\n";
httpd_handle_t stream_httpd = NULL;
httpd_handle_t camera_httpd = NULL;
#if CONFIG_ESP_FACE_DETECT_ENABLED
static int8_t detection_enabled = 0;
// #if TWO_STAGE
// static HumanFaceDetectMSR01 s1(0.1F, 0.5F, 10, 0.2F);
// static HumanFaceDetectMNP01 s2(0.5F, 0.3F, 5);
// #else
// static HumanFaceDetectMSR01 s1(0.3F, 0.5F, 10, 0.2F);
// #endif
#if CONFIG_ESP_FACE_RECOGNITION_ENABLED
static int8_t recognition_enabled = 0;
static int8_t is_enrolling = 0;
#if QUANT_TYPE
// S16 model
FaceRecognition112V1S16 recognizer;
#else
// S8 model
FaceRecognition112V1S8 recognizer;
#endif
#endif
#endif
typedef struct {
size_t size; //number of values used for filtering
size_t index; //current value index
size_t count; //value count
int sum;
int *values; //array to be filled with values
} ra_filter_t;
static ra_filter_t ra_filter;
static ra_filter_t *ra_filter_init(ra_filter_t *filter, size_t sample_size) {
memset(filter, 0, sizeof(ra_filter_t));
filter->values = (int *)malloc(sample_size * sizeof(int));
if (!filter->values) {
return NULL;
}
memset(filter->values, 0, sample_size * sizeof(int));
filter->size = sample_size;
return filter;
}
#if ARDUHAL_LOG_LEVEL >= ARDUHAL_LOG_LEVEL_INFO
static int ra_filter_run(ra_filter_t *filter, int value) {
if (!filter->values) {
return value;
}
filter->sum -= filter->values[filter->index];
filter->values[filter->index] = value;
filter->sum += filter->values[filter->index];
filter->index++;
filter->index = filter->index % filter->size;
if (filter->count < filter->size) {
filter->count++;
}
return filter->sum / filter->count;
}
#endif
#if CONFIG_ESP_FACE_DETECT_ENABLED
#if CONFIG_ESP_FACE_RECOGNITION_ENABLED
static void rgb_print(fb_data_t *fb, uint32_t color, const char *str) {
fb_gfx_print(fb, (fb->width - (strlen(str) * 14)) / 2, 10, color, str);
}
static int rgb_printf(fb_data_t *fb, uint32_t color, const char *format, ...) {
char loc_buf[64];
char *temp = loc_buf;
int len;
va_list arg;
va_list copy;
va_start(arg, format);
va_copy(copy, arg);
len = vsnprintf(loc_buf, sizeof(loc_buf), format, arg);
va_end(copy);
if (len >= sizeof(loc_buf)) {
temp = (char *)malloc(len + 1);
if (temp == NULL) {
return 0;
}
}
vsnprintf(temp, len + 1, format, arg);
va_end(arg);
rgb_print(fb, color, temp);
if (len > 64) {
free(temp);
}
return len;
}
#endif
static void draw_face_boxes(fb_data_t *fb, std::list<dl::detect::result_t> *results, int face_id) {
int x, y, w, h;
uint32_t color = FACE_COLOR_YELLOW;
if (face_id < 0) {
color = FACE_COLOR_RED;
} else if (face_id > 0) {
color = FACE_COLOR_GREEN;
}
if (fb->bytes_per_pixel == 2) {
//color = ((color >> 8) & 0xF800) | ((color >> 3) & 0x07E0) | (color & 0x001F);
color = ((color >> 16) & 0x001F) | ((color >> 3) & 0x07E0) | ((color << 8) & 0xF800);
}
int i = 0;
for (std::list<dl::detect::result_t>::iterator prediction = results->begin(); prediction != results->end(); prediction++, i++) {
// rectangle box
x = (int)prediction->box[0];
y = (int)prediction->box[1];
w = (int)prediction->box[2] - x + 1;
h = (int)prediction->box[3] - y + 1;
if ((x + w) > fb->width) {
w = fb->width - x;
}
if ((y + h) > fb->height) {
h = fb->height - y;
}
fb_gfx_drawFastHLine(fb, x, y, w, color);
fb_gfx_drawFastHLine(fb, x, y + h - 1, w, color);
fb_gfx_drawFastVLine(fb, x, y, h, color);
fb_gfx_drawFastVLine(fb, x + w - 1, y, h, color);
#if TWO_STAGE
// landmarks (left eye, mouth left, nose, right eye, mouth right)
int x0, y0, j;
for (j = 0; j < 10; j += 2) {
x0 = (int)prediction->keypoint[j];
y0 = (int)prediction->keypoint[j + 1];
fb_gfx_fillRect(fb, x0, y0, 3, 3, color);
}
#endif
}
}
#if CONFIG_ESP_FACE_RECOGNITION_ENABLED
static int run_face_recognition(fb_data_t *fb, std::list<dl::detect::result_t> *results) {
std::vector<int> landmarks = results->front().keypoint;
int id = -1;
Tensor<uint8_t> tensor;
tensor.set_element((uint8_t *)fb->data).set_shape({fb->height, fb->width, 3}).set_auto_free(false);
int enrolled_count = recognizer.get_enrolled_id_num();
if (enrolled_count < FACE_ID_SAVE_NUMBER && is_enrolling) {
id = recognizer.enroll_id(tensor, landmarks, "", true);
log_i("Enrolled ID: %d", id);
rgb_printf(fb, FACE_COLOR_CYAN, "ID[%u]", id);
}
face_info_t recognize = recognizer.recognize(tensor, landmarks);
if (recognize.id >= 0) {
rgb_printf(fb, FACE_COLOR_GREEN, "ID[%u]: %.2f", recognize.id, recognize.similarity);
} els
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源代码.rar (26个子文件)
源代码
ESP32SCAM
03 led
CameraWebServer
camera_index.h 148KB
app_httpd.cpp 40KB
.skip.esp32c3 0B
.skip.esp32h2 0B
camera_pins.h 8KB
CameraWebServer.ino 7KB
.skip.esp32c6 0B
partitions.csv 230B
01 led
CameraWebServer
camera_index.h 148KB
app_httpd.cpp 40KB
.skip.esp32c3 0B
.skip.esp32h2 0B
camera_pins.h 8KB
CameraWebServer.ino 7KB
.skip.esp32c6 0B
partitions.csv 230B
02 led
CameraWebServer
camera_index.h 148KB
app_httpd.cpp 40KB
.skip.esp32c3 0B
.skip.esp32h2 0B
camera_pins.h 8KB
CameraWebServer.ino 7KB
.skip.esp32c6 0B
partitions.csv 230B
app
xiaoChe.aia 81KB
xiaoChe.apk 2.69MB
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