In the configuration for Huge app on the ESP32 CAM, max flash is 3145728, max ram is 327680
Is this enough to run the application? The CAM board has a micro SD card slot available as well…
Great Idea!!
When you load the ESP32 board files there is a sample application, CameraWebServer, try that out first to make sure everything works.
Thanks!
Oh, you will also nee a USB to Serial adapter, like the FTDI board. Set the voltage switch to 5v.
See this link: https://randomnerdtutorials.com/program-upload-code-esp32-cam/
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Yeah that should be fine - will check if I have the board in!
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Hi Any update on the ESP32 CAM?
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@tcontrada I have the board laying around but haven’t gotten to use it yet. In the meantime we had a few users that have used the ESP32 CAM, incl. here: ESP32WROOM or ESP8266EX Node MCU Support and I’ve written an example to create a signal from a RGB565 frame buffer (which I think the ESP32 CAM uses): https://github.com/edgeimpulse/example-signal-from-rgb565-frame-buffer
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@janjongboom I just received an ESP32 cam. I’m trying to learn how the data is classified. Does the software support classification of live streaming data or is it just classifying single pictures/frames?
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Frame-by-frame, I don’t really get how you would do live streaming of the data. The buffer should remain the same until classification is done, then you can read from the camera again.
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Good point, I didn’t think of that. I lack that basic understanding on how data is read from the camera and how that data is structured which I’m currently researching.
I also read your github. So I need to convert the RGB565 to RGB888 then I can feed it into the static buffer?
@electronictechgreg Yes, just use the example repo to turn the RGB565 frame buffer into a signal_t structure. You then ask the classifier to classify the signal. Then you get predictions, and you can take the next photo!
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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.
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@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, 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0x5f5d52, 0x625f56, 0x625f57, 0x5d5a51, 0x625f56, 0x605c53, 0x58564d, 0x5c5d53, 0x5a5a53, 0x636159, 0x606057, 0x616258, 0x616158, 0x5f5f57, 0x606058, 0x67675f, 0x787162, 0x756e61, 0x766e61, 0x787162, 0x797262, 0x766f5d, 0x756e5d, 0x6c6558, 0x746d5c, 0x6a6356, 0x716a5b, 0x736b5e, 0x70685c, 0x766e60, 0x746d5c, 0x746d5b, 0x6f685a, 0x746e5d, 0x6c6656, 0x696252, 0x6a6456, 0x6d6759, 0x665f52, 0x666053, 0x635d50, 0x645e51, 0x625e52, 0x646054, 0x5e5b4f, 0x5e594e, 0x615b50, 0x625f53, 0x615d52, 0x5d5d50, 0x646258, 0x5e5a4f, 0x5f5b52, 0x686559, 0x5e5b50, 0x626156, 0x5f5f58, 0x615f56, 0x626258, 0x66665c, 0x66665b, 0x67675e, 0x6a6961, 0x6e6e63, 0x726b5c, 0x71695d, 0x6f675c, 0x70685a, 0x6d6557, 0x797361, 0x766e5f, 0x71695d, 0x6c6557, 0x716b5b, 0x6e675a, 0x70695d, 0x756f62, 0x6f675c, 0x6f6758, 0x6f6857, 0x736d5c, 0x6a6355, 0x645d50, 0x6e6758, 0x6b6556, 0x686455, 0x635e52, 0x645e51, 0x666054, 0x635e52, 0x625e52, 0x615d51, 0x5b574c, 0x635e54, 0x635f54, 0x645e54, 0x615d52, 0x5b594d, 0x666357, 0x666358, 0x615e55, 0x6a665c, 0x6c6a5d, 0x6c6b61, 0x6d6b61, 0x6f6d63, 0x717067, 0x6f6f65, 0x6b6a60, 0x6d6c63, 0x6b6a62, 0x65655f, 0x6a6455, 0x676054, 0x726c5c, 0x776f5f, 0x6e6658, 0x726b5b, 0x6d6457, 0x736c5d, 0x756f5e, 0x766e60, 0x726b5e, 0x706a5c, 0x676053, 0x635c4f, 0x686054, 0x6c6656, 0x726b5a, 0x696152, 0x696254, 0x6a6454, 0x6e6858, 0x696258, 0x665f54, 0x6a6457, 0x655f52, 0x655f53, 0x635e53, 0x615d51, 0x615d52, 0x5f5c51, 0x696559, 0x655f55, 0x676358, 0x676358, 0x68655a, 0x6a695d, 0x6e6a60, 0x6f6d64, 0x6e6c60, 0x726f63, 0x716d62, 0x716d63, 0x6c6960, 0x626058, 0x66635b, 0x58564f, 0x55554e, 0x55544e, 0x777061, 0x716a5a, 0x696254, 0x6e675a, 0x5f5a4f, 0x6b6555, 0x6e6656, 0x726a5b, 0x6f6858, 0x696255, 0x6f685a, 0x696154, 0x625b4f, 0x6d6557, 0x6c6657, 0x645e51, 0x6d6656, 0x6d6656, 0x675f51, 0x696254, 0x676154, 0x6c6357, 0x726a5f, 0x6b6658, 0x676153, 0x645f53, 0x6c675c, 0x6c685c, 0x6e6a5e, 0x706a5d, 0x736e62, 0x737165, 0x726f63, 0x6a675b, 0x6c685b, 0x6f6b5e, 0x6b665a, 0x655f56, 0x5b574e, 0x5d584e, 0x6f695f, 0x71685e, 0x73695d, 0x6a6359, 0x7d766c, 0x746c60, 0x796e61, 0x776c5f, 0x6b6356, 0x6c6457, 0x615b4e, 0x645d52, 0x615b51, 0x686253, 0x726b5a, 0x726b5d, 0x676153, 0x655f50, 0x686053, 0x635d51, 0x655d51, 0x6d645a, 0x6d675a, 0x645f52, 0x6a6356, 0x686152, 0x6e6758, 0x6b6556, 0x676152, 0x6a6256, 0x6c6459, 0x70685c, 0x746d60, 0x6d675a, 0x6c675a, 0x6f6a5e, 0x6a6757, 0x706b5d, 0x666359, 0x57554c, 0x5f5b51, 0x5b574e, 0x5a574d, 0x555046, 0x585247, 0x5d564b, 0x555045, 0x565048, 0x5e5650, 0x5e554c, 0x5e544a, 0x534b43, 0x534c46, 0x4c4942, 0x48423b, 0x3e3b35, 0x645b50, 0x6c6358, 0x6f675b, 0x655e53, 0x625c4f, 0x70695b, 0x6c6354, 0x6d6756, 0x696256, 0x6d6558, 0x6e6658, 0x6a6255, 0x696156, 0x675f54, 0x5b564a, 0x5d5b4e, 0x615e52, 0x5f594f, 0x585249, 0x575347, 0x575348, 0x4f4b42, 0x4c4740, 0x49483f, 0x46423b, 0x3c3b35, 0x373832, 0x373832, 0x2e2f29, 0x2b2b28, 0x202121, 0x1a1a1b, 0x1d1d1d, 0x18181a, 0x161719, 0x141516, 0x151617, 0x171618, 0x171419, 0x17161a, 0x15141a, 0x131419, 0x131518, 0x151419, 0x151318, 0x141316, 0x151419, 0x121316
};
/**
* @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).
1 Like
I’m not sure how much RAM is usable, but I’d try:
- Resize to 48x48
- Pick the MobileNetV2 0.05 transfer learning model
- Make sure to enable EON when creating the C++ library
And see if that works, then start making the model larger again.
2 Likes
@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
1 Like
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’.