Chip | YOLO11N_S8_V1 | YOLO11N_S8_V2 | YOLO11N_S8_V3 |
---|---|---|---|
ESP32-S3 | |||
ESP32-P4 |
yolo11n_s8_v1_s3
and yolo11n_s8_v1_p4
use 8bit default configuration quantization.yolo11n_s8_v2_p4
uses Mixed-Precision + Horizontal Layer Split Pass Quantization.yolo11n_s8_v3_s3
and yolo11n_s8_v3_p4
use Quantization-Aware Training.name | input(hwc) | preprocess(us) | model(us) | postprocess(us) |
---|---|---|---|---|
yolo11n_s8_v1_s3 | 640 * 640 * 3 | 207893 | 26919376 | 58994 |
yolo11n_s8_v3_s3 | 640 * 640 * 3 | 207892 | 26950089 | 58400 |
yolo11n_s8_v1_p4 | 640 * 640 * 3 | 105753 | 3109475 | 16610 |
yolo11n_s8_v2_p4 | 640 * 640 * 3 | 105758 | 3627073 | 16644 |
yolo11n_s8_v3_p4 | 640 * 640 * 3 | 105756 | 3104007 | 16178 |
COCODetect
accepts a COCODetect::model_type_t
parameter. It has a default value determined by model type option in menuconfig.
COCODetect
Cpp
COCODetect *detect = new COCODetect();
Cpp
// use YOLO11N_S8_V1
COCODetect *detect = new COCODetect(COCODetect::YOLO11N_S8_V1);
// use YOLO11N_S8_V2
// COCODetect *detect = new COCODetect(COCODetect::YOLO11N_S8_V2);
// use YOLO11N_S8_V3
// COCODetect *detect = new COCODetect(COCODetect::YOLO11N_S8_V3);
Note
If mutiple models is enabled in menuconfig, the default value is the first one. Pass in an explicit parameter to COCODetect
to use one of them.
Cpp
dl::image::img_t img = {.data=DATA, .width=WIDTH, .height=HEIGHT, .pix_type=PIX_TYPE};
std::list<dl::detect::result_t> &res = detect->run(img);
More details, see dl::image::img_t
and dl::detect::result_t
.
See Kconfig.
These options determines which models will be enabled.
Note
This component supports to load model from three different locations.
Note
partition.csv
must contain a partition named coco_det
, and the partition should be big enough to hold the model file.When model locates in sdcard, you can change the model directory relative to the sdcard mount point.
The default value of this option is models/s3
for ESP32S3 and models/p4
for ESP32P4.
When using default value, just copy models folder to sdcard root directory.
Note
Do not change the model name when copy the models to sdcard.
bf2ee2cbdc18dd43d415ced66a75c6fc0b8247a3
idf.py add-dependency "espressif/coco_detect^0.1.0"