uploaded 1 month ago
esp-dl is a lightweight and efficient neural network inference framework designed specifically for ESP series chips.
19 examples
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how_to_deploy_streaming_model
1
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cat_detect
A simple image inference example using ``cat.jpg`` for testing, demonstrating detection results before and after int8 quantization.
226.36 KB
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color_detect
A simple image inference example for color detection.
13.23 KB
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dog_detect
A simple image inference example using a dog image for detection with configurable options for model components.
633.70 KB
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hand_detect
A simple image inference example using hand detection, with results shown before and after quantization.
365.57 KB
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hand_gesture_recognition
A simple image inference example for recognizing 10 hand gestures plus a 'no_hand' category using the HaGRID dataset.
750.97 KB
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human_face_detect
A simple image inference example for human face detection, with configurable options for models.
42.52 KB
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human_face_recognition
A simple image inference example for human face recognition using ESP-IDF, integrating face detection and feature extraction models.
102.67 KB
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mobilenetv2_cls
This is a simple image inference example for IMAGENET classification using ESP32 chips.
38.99 KB
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pedestrian_detect
A simple image inference example for pedestrian detection using ESP-IDF. It includes configurable model options.
96.93 KB
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speaker_verification
A simple audio inference example for speaker verification with predefined audio samples and configurable options.
681.76 KB
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yolo11_detect
A simple image inference example using Yolo11 to detect objects in images, showcasing results before and after quantization.
670.34 KB
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yolo11_pose
A simple image inference example using Yolo11 for pose detection on ESP32-P4 with specific configurations.
266.98 KB
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yolo26_detect
This example runs quantized YOLOv26n inference on Espressif SoCs, supporting any YOLOv26 model configuration.
3.21 MB