uploaded 3 weeks ago
esp-dl is a lightweight and efficient neural network inference framework designed specifically for ESP series chips.
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how_to_deploy_streaming_model
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cat_detect
A simple image inference example that detects cats using a test image and supports int8 quantization on ESP32-P4.
226.26 KB
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dog_detect
A simple image inference example using dog.jpg for testing.
634.33 KB
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hand_detect
A simple image inference example that detects hands using a test image and supports int8 quantization on ESP32-P4.
367.67 KB
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hand_gesture_recognition
A simple image inference example that recognizes 10 hand gestures plus a "no_hand" category.
751.48 KB
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human_face_detect
A simple image inference example for detecting human faces.
43.03 KB
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mobilenetv2_cls
A simple image inference example that classifies a built-in cat image and benchmarks single- and multi-core latency.
40.58 KB
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pedestrian_detect
A simple image inference example for pedestrian detection.
97.44 KB
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person_reid
A simple image inference example for pedestrian detection and person re-identification feature extraction.
281.21 KB
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pp_ocr_v6
An ESP32-P4 image inference example based on PP-OCRv6. It performs on-device text detection and recognition.
657.34 KB
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speaker_verification
A simple audio inference example that verifies whether samples come from the same speaker using cosine similarity.
683.37 KB
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yolo11_detect
A simple YOLO11 image inference example using bus.jpg, demonstrating FP32 and INT8 quantized detection.
399.39 KB
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yolo11_pose
A simple image inference example using bus.jpg for testing.
265.43 KB
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yolo11_seg
A simple image inference example using YOLO11 segmentation with bus.jpg on ESP32 devices.
1.14 MB
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yolo26_detect
This is a complete end-to-end example for running quantized YOLOv26n inference on Espressif SoCs.
3.21 MB