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espressif
/esp-dl
3.3.6
Latest
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uploaded 13 hours ago
esp-dl is a lightweight and efficient neural network inference framework designed specifically for ESP series chips.
Readme
Dependencies
3
Dependents
13
Examples
19
Versions
24
19 examples
how_to_deploy_streaming_model
1
test_streaming_model
129.10 KB
cat_detect
A simple image inference example using `cat.jpg` for testing to demonstrate object detection results.
226.87 KB
color_detect
A simple image inference example for color detection.
13.26 KB
dog_detect
A simple image inference example using dog.jpg for testing, showcasing detection results before and after quantization.
634.21 KB
hand_detect
A simple image inference example using hand detection with configurable model options for ESP32 devices.
367.67 KB
hand_gesture_recognition
A simple image inference example supporting 10 hand gestures and a "no_hand" category using the HaGRID dataset.
751.48 KB
how_to_run_model
12.84 KB
human_face_detect
A simple image inference example for human face detection using ESP-IDF with configurable options.
43.03 KB
human_face_recognition
A simple example for human face recognition using image inference. It supports models for face detection and feature extraction.
103.18 KB
mobilenetv2_cls
A simple image inference example for IMAGENET classification that outputs category scores.
39.50 KB
model_in_flash_partition
10.74 KB
model_in_flash_rodata
10.88 KB
model_in_sdcard
10.71 KB
motion_detect
52.64 KB
pedestrian_detect
A simple image inference example for pedestrian detection using ESP-IDF.
97.44 KB
speaker_verification
A simple audio inference example that compares audio samples from different speakers using cosine similarity.
682.25 KB
yolo11_detect
A simple image inference example using Yolo11 for object detection with quantization results shown.
399.39 KB
yolo11_pose
A simple image inference example using Yolo11 Pose with ESP32-P4, testing with a default image and settings.
267.49 KB
yolo26_detect
This example demonstrates YOLOv26n inference on Espressif SoCs with optimizations for various custom models.
3.21 MB