Segment-Anything-2.1-RKNN2

4
license:agpl-3.0
by
happyme531
Other
OTHER
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Quick Summary

AI model with specialized capabilities.

Code Examples

使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bashonnx
pip install numpy<2 pillow matplotlib opencv-python onnxruntime rknn-toolkit-lite2
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
使用方法bash
python test_rknn.py
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. 加载原始图片
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
模型转换bashonnx
pip install numpy<2 onnxslim onnxruntime rknn-toolkit2 sam2
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...
pythononnx
def main():
    # 1. Load original image
    path = "dog.jpg"
    orig_image, input_image, (scale, offset_x, offset_y) = load_image(path)
    decoder_path = "sam2.1_hiera_small_decoder.onnx"
    encoder_path = "sam2.1_hiera_small_encoder.rknn"
    ...

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