本文记录Python中二维高斯核的生成方法。 生成思路 使用cv2.getGaussianKernel(ksize, sigma[, ktype])函数 该函数用于生成一维高斯核 生成一维高斯核后乘以自己的转置得到二维高斯核 核心函数 cv2.getGaussianKernel(ksize, sigma[, ktype]),函数生成一维高斯核 官方函数文档 参数说明 公式: Gi=α∗e−(i−...
生成思路 使用 cv2.getGaussianKernel(ksize, sigma[, ktype]) 函数 该函数用于生成一维高斯核 生成...
importtorchimporttorch.nn.functionalasFimportnumpyasnpimportmatplotlib.pyplotaspltdefgaussian_kernel(size,sigma):"""生成高斯核"""x=np.linspace(-size//2+1,size//2,size)y=np.linspace(-size//2+1,size//2,size)x,y=np.meshgrid(x,y)g=np.exp(-(x**2+y**2)/(2*sigma**2))returng/g....
values = np.vstack([x, y]) kernel = st.gaussian_kde(values) f = np.reshape(kernel(positions).T, xx.shape) return xx, yy, f 1. 2. 3. 4. 5. 6. 7. 8. 9. fig = plt.figure(figsize=(8,6)) fig.subplots_adjust(wspace = 0.5, hspace = 0.5) plt.subplot2grid((1,4),(0,...
python main.py 正常的话会有在代码所在得文件夹生成一些结果: 2. 关键代码解释 2.1 函数generate_2D_gaussian_splatting: 2.1.1单独运行该函数的例子: python test_generate_2D_gaussian_splatting.py 例子中生成了4个高斯核: test_generate_2D_gaussian_splatting 结果 ...
pythonjupyter-notebookpytorchgaussian-kernelpytorch-implementationgaussian-splatting2d-gaussian-splatting UpdatedMar 3, 2025 Jupyter Notebook 🏠[ECCV 2024] GaussianImage: 1000 FPS Image Representation and Compression by 2D Gaussian Splatting image-compressionimage-representationgaussian-splatting2d-gaussian-sp...
sepFilter2D(src, ddepth, kernelX, kernelY[, dst[, anchor[, delta[, borderType]]]) 比较filter2D()和sepFilter2D() 的计算速度: img = np.random.rand(1000,1000) row = cv2.getGaussianKernel(7, -1) col = cv2.getGaussianKernel(5, -1) kernel = np.dot(col[:], row[:].T) img2 ...
This 3D tumour mask was then smoothed with a Gaussian kernel (sigma = 1.0). The resulting values were then used as input for the marching cubes algorithm76,77 to generate a surface mesh for the tumour volume. We used the scikit-image implementation (skimage.measure.marching_cubes) of ...
gaussians.training_setup(opt) gaussians.training_setup(opt, neural_renderer) ema_neural_renderer = ExponentialMovingAverage(neural_renderer.parameters(), decay=0.95) if checkpoint: (model_params, first_iter) = torch.load(checkpoint) gaussians.restore(model_params, opt) ...
2d density chart withMatplotlib 2D densities are computed thanks to thegaussian_kde()function and plotted thanks with thepcolormesh()function ofmatplotlib(). Basic 2d density with bins customization Control the color in the 2d density. Black and white, color scale legend....