I watched your video on Adding sight to your sensors. When I was talking about streaming what I meant was live classification like you did in the video. So that answered that question for me.
As for the ESP32 cam, apparently I can output in RGB888 format using the fmt2rgb888 function from the esp_camera.h library. Then convert it to a signal_t structure then feed it into the classifier. I think I got it.
@janjongboom I apologize if this issue has been resolved and I just could not find a resolution. I uploaded static_buffer sketch to ESP32 Cam board and getting ‘panic’ exception. When I decoded the trace I found this
As per all the suggestion in this thread, I converted feature to RGB888 following your repo. I have tested basic web camera code with this board which is working. So my board and fine. I also uploaded the same sketch to Nano BLE sense and it worked. Just can’t get it working with ESP32 Cam. Here is my code.
/* Edge Impulse Arduino examples
* Copyright (c) 2020 EdgeImpulse Inc.
*
* Permission is hereby granted, 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.
*/
/* Includes ---------------------------------------------------------------- */
#include <animal_faces_inference.h>
#define CUTOUT_COLS EI_CLASSIFIER_INPUT_WIDTH
#define CUTOUT_ROWS EI_CLASSIFIER_INPUT_HEIGHT
#define FRAME_BUFFER_COLS 48
#define FRAME_BUFFER_ROWS 48
uint16_t frame_buffer[FRAME_BUFFER_COLS * FRAME_BUFFER_ROWS] = { 0 };
const int cutout_row_start = (FRAME_BUFFER_ROWS - CUTOUT_ROWS) / 2;
const int cutout_col_start = (FRAME_BUFFER_COLS - CUTOUT_COLS) / 2;
static const float features[] = {
0xaf9118, 0xcea714, 0xdbb618, 0xd5b613, 0xcbb10d, 0xd7bc0e, 0xdfc017, 0xdcb924, 0xbea32e, 0xc3af40, 0xcdba5d, 0xc5b467, 0xbcb57c, 0xb4b48f, 0xaaaa81, 0x9ea483, 0x95a491, 0x9db3b4, 0x9eb5bc, 0x96acb0, 0x8f9683, 0x858366, 0x6e6b51, 0x646249, 0x6c6a54, 0x5f5c4b, 0x5c5948, 0x555140, 0x564e3b, 0x655b43, 0x655d43, 0x685e46, 0x6a614a, 0x6b634c, 0x72674d, 0x797052, 0x827756, 0x847a5c, 0x897f63, 0x8c8261, 0x9d9777, 0xa9ada5, 0x9e9f8c, 0x9c9477, 0x9a8f6a, 0x9b8e66, 0x9a8c64, 0x9a8d66, 0xb18e23, 0xd1a320, 0xc6a62b, 0xb09c21, 0xc0a517, 0xd4b80e, 0xceb207, 0xe4c114, 0xe6c01d, 0xdbbc17, 0xdfbf18, 0xdec019, 0xd7b81e, 0xd4b72d, 0xc3a92c, 0xc5a937, 0xb4a143, 0x9d985a, 0x94925d, 0x918a5a, 0x94823a, 0x8f8137, 0x655d36, 0x524e34, 0x524d38, 0x534f3a, 0x545240, 0x444134, 0x464237, 0x4c473a, 0x524c3d, 0x534c3d, 0x595241, 0x5b5542, 0x605844, 0x685e48, 0x71674d, 0x72674f, 0x796d52, 0x7e7255, 0x887d5a, 0x9b9677, 0x928864, 0x8d7f5c, 0x8c7e5d, 0x90835f, 0x968761, 0x93875d, 0xb08d37, 0xa6852f, 0x9a8426, 0x8f7d2c, 0xb89c22, 0xbea216, 0xb0990c, 0xceaf15, 0xe5c01f, 0xd7b70b, 0xdab918, 0xd9b81f, 0xddc017, 0xdabf16, 0xd3b71c, 0xe1c02d, 0xc9ae25, 0xc2a71f, 0xc7a826, 0xbba120, 0xc0a324, 0xaf9625, 0x95812a, 0x8c782c, 0x5d542f, 0x4c4731, 0x554f34, 0x4c4632, 0x4d4935, 0x4a4737, 0x4c4839, 0x4c473b, 0x4f4b3c, 0x544f3f, 0x565140, 0x635c44, 0x6c664b, 0x665e4c, 0x706750, 0x807558, 0x898160, 0x858067, 0x898170, 0x80755e, 0x82765e, 0x84775d, 0x897a5d, 0x8c7a5d, 0xc4a819, 0xceb026, 0xc6aa19, 0xc3a319, 0xcda814, 0xd4b109, 0xcfaf12, 0xbc9d14, 0xc6ac11, 0xbaa50f, 0xcaad0f, 0xd8b50e, 0xdbbc0c, 0xd8bd0c, 0xccb214, 0xd4b718, 0xdabd0f, 0xdbbd10, 0xddbd1e, 0xd6ba18, 0xd7b718, 0xd8b81e, 0xcfb026, 0xd5b02b, 0xc2a224, 0xab9222, 0xa99022, 0xa58b24, 0x998323, 0x927a31, 0x745f36, 0x6e5c39, 0x605537, 0x544d3a, 0x5a553c, 0x5a553e, 0x5f5a41, 0x686347, 0x706951, 0x817958, 0x8c855f, 0x8b8461, 0x847e6b, 0x7c735d, 0x7a6c59, 0x7e6f5b, 0x84725a, 0x897359, 0xc3ac02, 0xd3b50a, 0xcfab14, 0xcfaa0e, 0xd7b60a, 0xd7b711, 0xdbb90c, 0xd4b506, 0xcdb405, 0xb6a403, 0xb8a007, 0xc3a90b, 0xaf9f05, 0xc7b204, 0xcab10f, 0xcaae12, 0xd5ba08, 0xddc009, 0xe2c114, 0xd6b316, 0xdfbd14, 0xe5c123, 0xebc632, 0xe1bd27, 0xdcba21, 0xdeb922, 0xdbb325, 0xd6ae23, 0xcaa323, 0xd3aa30, 0xcba53f, 0xc69e40, 0xc19f40, 0x9f8636, 0x988137, 0x8d793b, 0x6d5f3e, 0x6c6140, 0x766945, 0x7a6d4c, 0x7a6e4c, 0x88825d, 0x7a745e, 0x756a54, 0x766854, 0x796a55, 0x837054, 0x8b7354, 0xc1a702, 0xc8ac04, 0xc7a117, 0xc8992c, 0xc9a115, 0xbc9c11, 0xcdb20a, 0xcdb701, 0xcab504, 0xc5b003, 0xccae09, 0xc8a90b, 0xc3aa0a, 0xd0b604, 0xd9be07, 0xdcbc0e, 0xc8ac0e, 0xc5ad0a, 0xccb60b, 0xc2b00b, 0xcbb609, 0xd2b415, 0xd3b31f, 0xd4b419, 0xd7b51d, 0xd6b328, 0xd7b525, 0xd4b122, 0xd4b129, 0xceae2c, 0xd1af2d, 0xdbb543, 0xd7b448, 0xd3b040, 0xd1ae42, 0xd7b14e, 0xcaa24f, 0xbb9749, 0xa88d45, 0xa38648, 0xae8f4c, 0x958651, 0x817753, 0x74664d, 0x736650, 0x776853, 0x7f6b51, 0x897152, 0xa59009, 0xb99e05, 0xb89313, 0xc9992c, 0xc99e23, 0xc3a014, 0xcfb219, 0xbda70d, 0xc5aa0e, 0xceb114, 0xb9a416, 0xceb214, 0xc29e17, 0xc3ab19, 0xc4ac0f, 0xd2b110, 0xbc981a, 0xa88a1b, 0xb29f0e, 0xbfac0a, 0xb8a706, 0xc7ac07, 0xbaa10b, 0xbfa514, 0xd0b215, 0xc2a612, 0xc0a60e, 0xc5ac13, 0xbca020, 0xaf9525, 0xbe9d1f, 0xc7ac26, 0xceb42f, 0xcdb131, 0xc7ac2f, 0xc7a93a, 0xc9aa41, 0xc6aa42, 0xc6a943, 0xbea143, 0xb89c43, 0xbd9f47, 0xb3974c, 0xad924d, 0xac8f4c, 0xa58a4e, 0xaa8e51, 0xb19153, 0x9f890e, 0xbd990d, 0xb99218, 0xa88827, 0xb89b26, 0xb0932d, 0xbb9727, 0xb39918, 0xa99315, 0xc1a11d, 0x938221, 0xad9524, 0xab9023, 0x816f2c, 0x8f792a, 0xab8f23, 0x9e8624, 0x9f8329, 0xc9b11a, 0xa99a12, 0x8b7a19, 0xa58f11, 0xb7a107, 0xb39712, 0xc5a718, 0xb29917, 0xac9516, 0xa9931c, 0xa2892a, 0x96852b, 0x978429, 0x988a25, 0xa79424, 0xaa952d, 0xa58e38, 0x9b8735, 0x937e38, 0x8f7e38, 0x9d8a3a, 0x9e863b, 0x8c7e3c, 0xa58e41, 0xbb9948, 0xc2a14e, 0xc5a34c, 0xbf9c4a, 0xc1a04d, 0xc6a450, 0xa88e18, 0xc39d15, 0xc8a40c, 0xa8841e, 0xbd9320, 0xb29327, 0xbfa224, 0xbba515, 0xbba613, 0xc9b315, 0xbaa021, 0xb69129, 0x9f8025, 0x967722, 0x977223, 0xc29130, 0x997b2a, 0x6f6025, 0x988824, 0xa6941f, 0x846c27, 0x927429, 0xb48e23, 0xb78f2a, 0xbd942b, 0xb9922e, 0xb18d2d, 0xc29d3c, 0xbf9c3c, 0xa28325, 0x967c30, 0x967f36, 0x997b2c, 0xa58733, 0xa2863f, 0xa7843a, 0xbc923e, 0xb58b40, 0xa2813d, 0x9a7f40, 0x9a8040, 0x947d40, 0x9c8244, 0x9f8645, 0xa28847, 0xab8b49, 0xb68f4b, 0xba974f, 0xa38a1c, 0xa08c11, 0xbfab02, 0xcaaf0a, 0xbfa50f, 0xbba90d, 0xb8ab09, 0x988612, 0xa98c27, 0xc0a52c, 0xb8a41c, 0xc4a918, 0xb69224, 0xba9c0e, 0xcda90f, 0xdba428, 0xd29c33, 0xaf862c, 0xb0872c, 0xca9b2f, 0xc89329, 0xd8a233, 0xd29e32, 0xcd983a, 0xd29d36, 0xcd982e, 0xc39232, 0xc39933, 0xb0922c, 0xac8d22, 0xb6962a, 0xaa892f, 0xa6812b, 0xa7832f, 0xa48130, 0xaf8633, 0xc6953b, 0xb88f40, 0xa0833e, 0x9e8541, 0x998342, 0xa08848, 0xa38946, 0x9e8545, 0xa38748, 0xac8d4c, 0xb38f4d, 0xbb984f, 0xa28219, 0x847911, 0x998e09, 0x989409, 0x938c10, 0xa99612, 0xad9813, 0xbb9e15, 0xc09c2f, 0xbea32e, 0x9c9312, 0xa59906, 0xab9b0c, 0x7c750c, 0xb1a00c, 0xdbbd0f, 0xd1af13, 0xc3a119, 0xc2a415, 0xc3a01c, 0xb1941b, 0xd4a523, 0xca9429, 0xc79733, 0xb79524, 0xb8901d, 0xbc8f24, 0xb68a30, 0xae9124, 0xa08a1a, 0xa89016, 0xb09119, 0xa98629, 0xa38928, 0xa5842f, 0xa07f30, 0xb38b36, 0xb99239, 0xa5843a, 0xaa8e3e, 0xab923f, 0xad8f47, 0xaf8b45, 0xb59047, 0xb5944a, 0xb9964c, 0xb8964a, 0xba9d4d, 0xa3850c, 0xae8e08, 0xbf9f07, 0x9b8808, 0x69680b, 0x83741b, 0x90801f, 0xb2951a, 0xa68826, 0xa29224, 0xa39b13, 0xaca007, 0xbba901, 0x91840e, 0x9f9014, 0xa59a08, 0xb4ad01, 0xb0a503, 0xa89b04, 0xae9e0d, 0xb6a111, 0xbc9c1c, 0xb69023, 0xaa921c, 0x918f0e, 0xae9f08, 0xb49f12, 0xab921f, 0x9e8a19, 0x9f9115, 0x9a8a19, 0xa18f18, 0x837925, 0x8f8625, 0x978428, 0x957d2c, 0x9d7b30, 0xab8833, 0xb08d37, 0xa38b38, 0xa38f3a, 0xac8f39, 0xaa8743, 0xad884a, 0xb08d4a, 0xb9994b, 0xb19a49, 0xaf964e, 0x9b8110, 0x806913, 0x9a8109, 0xb99807, 0x8a7710, 0x88761e, 0x938022, 0x978317, 0xa0901b, 0x827b18, 0x706b13, 0x9f8f0e, 0xab9111, 0xad9e0a, 0xa39d0e, 0x988c18, 0xa8a00b, 0xb0ab06, 0xaa9c06, 0xbb9f17, 0xb9a511, 0x998b0d, 0x9e9011, 0x868112, 0x8c8911, 0x958f08, 0x817914, 0x8d831a, 0x968025, 0x7e7226, 0x7c7322, 0xa4911f, 0x978829, 0x958a2b, 0x8c812b, 0x8c7830, 0x987d30, 0x9e8037, 0x9a7c3b, 0x8b743a, 0x917b42, 0x988146, 0x9b814a, 0x9e8151, 0xa08654, 0xa08a53, 0xa99452, 0xae9456, 0x8c7218, 0x896b1a, 0x907412, 0xa9890a, 0xac8c0f, 0xa38517, 0xa58322, 0x877417, 0x837a11, 0x928a0b, 0x8d7f0f, 0x907f12, 0x9e8215, 0xb49f07, 0xaa9c0c, 0x978616, 0x958311, 0xa59211, 0x9e8412, 0xaf9117, 0xbea20e, 0xa38d08, 0x9f8e09, 0x746c12, 0x726b13, 0x898011, 0x948014, 0x907813, 0x977f20, 0x867127, 0x7c6823, 0x776822, 0x7e6c2a, 0x87782a, 0x87762b, 0x776c32, 0x867637, 0x937e40, 0x83733e, 0x87753f, 0x8f7a42, 0x9c854a, 0x947f4b, 0x917f54, 0x9e895b, 0xa18d60, 0xa79264, 0xaa9767, 0x8b7c0a, 0x988109, 0xa2850d, 0x957e0b, 0xa48e07, 0xa89305, 0xaf9309, 0xac8f06, 0x918106, 0x9a8907, 0x9c8d09, 0x988e0a, 0x928209, 0x8c7b0b, 0x8f7916, 0x896f1d, 0xa08419, 0xb19012, 0xa77f13, 0x9b7e0a, 0x967b00, 0x9b8802, 0xb39f0f, 0xac9523, 0x97872f, 0x83773a, 0x988740, 0x958036, 0x937e34, 0x9d843b, 0x8c7033, 0x706435, 0x7d6d33, 0x7a6f33, 0x928851, 0x716d35, 0x71682a, 0x7d7032, 0x736b35, 0x857b43, 0x867b46, 0x877c4a, 0x958754, 0xa59360, 0xb7a06e, 0xbaa571, 0xb2a176, 0xb8a87e, 0x786910, 0x877507, 0x948105, 0x837506, 0x958406, 0xa59203, 0x998905, 0xbc9e05, 0xa09003, 0x908206, 0x92820c, 0x8f810d, 0x907b0e, 0x957815, 0x997622, 0xa58123, 0xa7831c, 0xaf7d10, 0xa67712, 0x91792c, 0x9a8c5d, 0x888e76, 0x8f997f, 0x89938f, 0x879099, 0x8f989f, 0x929ba4, 0x909699, 0x90948f, 0x929592, 0x8d908c, 0x91958f, 0x9a9e93, 0xa0a299, 0xb4b3b8, 0x9b9a8f, 0xaaa282, 0xaa9f7b, 0x988d67, 0x92894f, 0x8b823f, 0x898048, 0x918a54, 0xad9d6b, 0xc7b17f, 0xc9b986, 0xc7b589, 0xcfbf92, 0xaa8d10, 0xa89202, 0xa68f04, 0x9c8707, 0x85750c, 0x6c6315, 0x6f660f, 0x73680b, 0xa49106, 0x998a06, 0xb09b05, 0x9a8906, 0x9d880d, 0xb29c0f, 0xab9613, 0x9a8112, 0x8a6f15, 0x8c7532, 0x8a846f, 0x7f909f, 0x6383a4, 0x52749d, 0x42638c, 0x37577e, 0x334f72, 0x304a6c, 0x304767, 0x314968, 0x354b6a, 0x384d6a, 0x3c4f6b, 0x40536c, 0x465972, 0x545e76, 0xa5a5b1, 0xded6da, 0xbeb8bd, 0xafabae, 0xb4b1ac, 0xcac4b4, 0xc5bfa1, 0xa6a06f, 0x908d56, 0x9b9366, 0xb9aa7e, 0xc1b58a, 0xd1c394, 0xe0ce9c, 0x81770d, 0x817607, 0xa28808, 0x86790a, 0x7c710e, 0x6a6510, 0x5d5a0f, 0x796f0c, 0x938305, 0x827c06, 0x827e06, 0x797509, 0x464a18, 0x55590b, 0x606903, 0x8b8b1c, 0x92946a, 0x8b9cb2, 0x6484a8, 0x3f6484, 0x3d5e6f, 0x3d5964, 0x3c525c, 0x364c56, 0x263a4f, 0x25364c, 0x26364a, 0x28384a, 0x293748, 0x2c3b4b, 0x3a4d56, 0x425559, 0x303f4a, 0x616670, 0xd1cac8, 0x798490, 0x4b677e, 0x516f87, 0x597389, 0x677788, 0x878e96, 0xbab8b2, 0xc1bca9, 0xa19d80, 0xa2997a, 0xaea487, 0xc0b393, 0xc7bc97, 0x76680d, 0x82710c, 0xa58212, 0x97810c, 0x81720f, 0x756c11, 0x726a0d, 0x76700f, 0x696a0e, 0x635c12, 0x625a1b, 0x7c7313, 0x615e21, 0x676a57, 0x6a7060, 0x8a999d, 0x8b9eb9, 0x5c788f, 0x365568, 0x3a525d, 0x3f5558, 0x3e5050, 0x3c4e51, 0x32444b, 0x243241, 0x232f3e, 0x283541, 0x25313d, 0x26313c, 0x2c3945, 0x384d56, 0x314650, 0x39414e, 0xbeb8b8, 0x808e9c, 0x305777, 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};
/**
* @brief Copy raw feature data in out_ptr
* Function called by inference library
*
* @param[in] offset The offset
* @param[in] length The length
* @param out_ptr The out pointer
*
* @return 0
*/
int raw_feature_get_data(size_t offset, size_t length, float *out_ptr) {
memcpy(out_ptr, features + offset, length * sizeof(float));
return 0;
}
void r565_to_rgb(uint16_t color, uint8_t *r, uint8_t *g, uint8_t *b) {
*r = (color & 0xF800) >> 8;
*g = (color & 0x07E0) >> 3;
*b = (color & 0x1F) << 3;
}
int cutout_get_data(size_t offset, size_t length, float *out_ptr) {
// so offset and length naturally operate on the *cutout*, so we need to cut it out from the real framebuffer
size_t bytes_left = length;
size_t out_ptr_ix = 0;
// read byte for byte
while (bytes_left != 0) {
// find location of the byte in the cutout
size_t cutout_row = floor(offset / CUTOUT_COLS);
size_t cutout_col = offset - (cutout_row * CUTOUT_COLS);
// then read the value from the real frame buffer
size_t frame_buffer_row = cutout_row + cutout_row_start;
size_t frame_buffer_col = cutout_col + cutout_col_start;
// grab the value and convert to r/g/b
uint16_t pixel = frame_buffer[(frame_buffer_row * FRAME_BUFFER_COLS) + frame_buffer_col];
uint8_t r, g, b;
r565_to_rgb(pixel, &r, &g, &b);
// then convert to out_ptr format
float pixel_f = (r << 16) + (g << 8) + b;
out_ptr[out_ptr_ix] = pixel_f;
// and go to the next pixel
out_ptr_ix++;
offset++;
bytes_left--;
}
// and done!
return 0;
}
/**
* @brief Arduino setup function
*/
void setup()
{
// put your setup code here, to run once:
Serial.begin(115200);
Serial.println("Edge Impulse Inferencing Demo");
}
/**
* @brief Arduino main function
*/
void loop()
{
ei_printf("Edge Impulse standalone inferencing (Arduino)\n");
if (sizeof(features) / sizeof(float) != EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE) {
ei_printf("The size of your 'features' array is not correct. Expected %lu items, but had %lu\n",
EI_CLASSIFIER_DSP_INPUT_FRAME_SIZE, sizeof(features) / sizeof(float));
delay(1000);
return;
}
ei_impulse_result_t result = { 0 };
// the features are stored into flash, and we don't want to load everything into RAM
signal_t features_signal;
features_signal.total_length = sizeof(features) / sizeof(features[0]);
//features_signal.get_data = &raw_feature_get_data;
features_signal.get_data = &cutout_get_data;
// invoke the impulse
EI_IMPULSE_ERROR res = run_classifier(&features_signal, &result, false /* debug */);
ei_printf("run_classifier returned: %d\n", res);
if (res != 0) return;
// print the predictions
ei_printf("Predictions ");
ei_printf("(DSP: %d ms., Classification: %d ms., Anomaly: %d ms.)",
result.timing.dsp, result.timing.classification, result.timing.anomaly);
ei_printf(": \n");
ei_printf("[");
for (size_t ix = 0; ix < EI_CLASSIFIER_LABEL_COUNT; ix++) {
ei_printf("%.5f", result.classification[ix].value);
#if EI_CLASSIFIER_HAS_ANOMALY == 1
ei_printf(", ");
#else
if (ix != EI_CLASSIFIER_LABEL_COUNT - 1) {
ei_printf(", ");
}
#endif
}
#if EI_CLASSIFIER_HAS_ANOMALY == 1
ei_printf("%.3f", result.anomaly);
#endif
ei_printf("]\n");
// human-readable predictions
for (size_t ix = 0; ix < EI_CLASSIFIER_LABEL_COUNT; ix++) {
ei_printf(" %s: %.5f\n", result.classification[ix].label, result.classification[ix].value);
}
#if EI_CLASSIFIER_HAS_ANOMALY == 1
ei_printf(" anomaly score: %.3f\n", result.anomaly);
#endif
delay(1000);
}
/**
* @brief Printf function uses vsnprintf and output using Arduino Serial
*
* @param[in] format Variable argument list
*/
void ei_printf(const char *format, ...) {
static char print_buf[1024] = { 0 };
va_list args;
va_start(args, format);
int r = vsnprintf(print_buf, sizeof(print_buf), format, args);
va_end(args);
if (r > 0) {
Serial.write(print_buf);
}
}
My model is trained in grayscale with 48x48 resolution.
Any thoughts please ?
You guys are incredible. I want to you know that I have successfully deployed the edge impulse project to the esp32cam development board (uninstall and re install Arduino and platform.local.txt helped a lot.
After copying raw data in the project and deploying it successfully, I didn’t see the desired result in the serial monitor. As shown in the figure below. Is it the wrong data I copied, or something else?
Hi @jiffy, it cannot allocate a buffer large enough to run the neural network calculations. How large is the model that you created (as it states on the Deployment page)? Probably pick a smaller transfer learning model or set the size of your image to a lower resolution (on Create impulse page).
I’m not sure how much RAM is usable, but I’d try:
And see if that works, then start making the model larger again.
@janjongboom thanks a lot. these suggestions really worked. now it can work well with the static_buffer. My problem is, if I want to read images in real time for classification, instead of using static_ buffer, is the size limit still in place?
@jifly, well, you’re limited by the amount of RAM and flash that can be used on the ESP32Cam, so yes, still in place (maybe even a bit less because you need to allocate a framebuffer for the video somewhere)… I think this is helpful too: https://github.com/edgeimpulse/example-signal-from-rgb565-frame-buffer
Hi, Jan.
I have a problem with the esp32 cam board as follows:
how to solve it please help me.
thank you, Rizki
Hi @rizkiosb your model is too big. You can swap out the transfer learning model for the 0.1 model for example via Impulse design > Transfer learning and then ‘Choose a different
model’.
@jifly Have you seen https://www.survivingwithandroid.com/tinyml-esp32-cam-edge-image-classification-with-edge-impulse/ ? It has a full code example for the ESP32Cam.
I didn’t notice this link before. I did it according to the link of rgb565 to rgb888. Great. I’ll refer to this. Thank you so much！@ janjongboom
hi, @janjongboom
after I run the buffer_static program an error message appears like this:
How to solve it please help me.
Thanks, Nena
Hi @Nenamd,
That a known Windows Arduino issue.
You can install the patch here: https://docs.edgeimpulse.com/docs/running-your-impulse-arduino#code-compiling-fails-under-windows-os
The alternative is to install Arduino IDE 2.0 beta, it should fix this issue.
Aurelien
Hi, @janjongboom @aurel
I want to ask, why does my program always stop here and the IP address doesn’t appear?
Thank you, Nena
Hi @Nenamd,
This could be linked to RAM limitation as suggested in messages in this thread. How big is your image model? Using 48x48 pixels images and MobileNet 0.05 version should work on this board, you can see this great article as mentioned by Jan: https://www.survivingwithandroid.com/tinyml-esp32-cam-edge-image-classification-with-edge-impulse/
Aurelien
thank you, @aurel for the answer. I’ve converted the image to 48x48 pixels and the MobileNet version to 0.05, as reviewed by the article provided by Jan. but the result is like that.
Nena
Looks like it could be some power supply issue, see this link.
Are you able to make the board work with the Arduino Blinky sketch?
Also if you can share your Edge Impulse project ID we can double check that everything is set up correctly.
Aurelien
Thank you, @aurel
I have tried using the static_buffer example and it works but from that article it doesn’t work.
I am very grateful if you can help me.
this is my Impulse Edge Project ID: 23879
Nena
Hi @aurel @janjongboom I want to ask again about the classification used by Edge Impulse, namely NN.
which one belongs to the NN?
CNN, ANN, or RNN?
thank you
Nena
