eads 开发者文档

EADS（English to Artificial Language Document Serializer）是一种开发者文档，旨在为开发者提供技术参考和指南。EADS的主要目标是帮助开发者快速了解和使用特定的技术、框架或软件。

EADS的开发者文档通常包含以下内容：
1. 引言和概述：文档会提供有关技术的简要介绍，包括其用途、特点和优势等。这部分内容旨在让开发者快速了解技术的基本知识。
2. 安装指南：文档将提供关于如何安装和配置技术的详细步骤。这包括依赖项的安装、环境设置和必要的配置等。
3. 快速入门指南：这是开发者文档中的重要部分，旨在为开发者提供一个简单的示例或教程，展示如何使用技术来完成常见的任务或实现特定的功能。
4. API参考：这部分包括技术的详细API文档，包括可用的类、方法、属性和常量等。这样，开发者可以了解和理解技术的各个方面，并更好地利用其功能。
5. 示例代码：文档通常提供一些实际的例子，展示如何使用技术来解决实际问题。这些示例代码可以帮助开发者更好地理解和应用技术。
6. 常见问题解答（FAQ）：文档还可能包含一些常见问题的答案，以便开发者能够快速解决一些常见的疑惑和问题。

总之，EADS开发者文档是一个为开发者提供技术参考和指导的文档。通过提供安装指南、快速入门指南、API参考、示例代码和FAQ等内容，EADS开发者文档帮助开发者更快地学习和使用特定的技术。

相关问题

ffmpeg version 2023-07-06-git-f00222e81f-essentials_build-www.gyan.dev Copyright (c) 2000-2023 the FFmpeg developers built with gcc 12.2.0 (Rev10, Built by MSYS2 project) configuration: --enable-gpl --enable-version3 --enable-static --disable-w32thr eads --disable-autodetect --enable-fontconfig --enable-iconv --enable-gnutls --e nable-libxml2 --enable-gmp --enable-bzlib --enable-lzma --enable-zlib --enable-l ibsrt --enable-libssh --enable-libzmq --enable-avisynth --enable-sdl2 --enable-l ibwebp --enable-libx264 --enable-libx265 --enable-libxvid --enable-libaom --enab le-libopenjpeg --enable-libvpx --enable-mediafoundation --enable-libass --enable -libfreetype --enable-libfribidi --enable-libharfbuzz --enable-libvidstab --enab le-libvmaf --enable-libzimg --enable-amf --enable-cuda-llvm --enable-cuvid --ena ble-ffnvcodec --enable-nvdec --enable-nvenc --enable-d3d11va --enable-dxva2 --en able-libvpl --enable-libgme --enable-libopenmpt --enable-libopencore-amrwb --ena ble-libmp3lame --enable-libtheora --enable-libvo-amrwbenc --enable-libgsm --enab le-libopencore-amrnb --enable-libopus --enable-libspeex --enable-libvorbis --ena ble-librubberband libavutil 58. 14.100 / 58. 14.100 libavcodec 60. 22.100 / 60. 22.100 libavformat 60. 10.100 / 60. 10.100 libavdevice 60. 2.101 / 60. 2.101 libavfilter 9. 8.102 / 9. 8.102 libswscale 7. 3.100 / 7. 3.100 libswresample 4. 11.100 / 4. 11.100 libpostproc 57. 2.100 / 57. 2.100 [in#0 @ 000001fd774d6780] Error opening input: No such file or directory

根据您提供的信息，您遇到了一个错误，提示“Error opening input: No such file or directory”。这个错误表明FFmpeg无法打开输入文件，因为文件不存在或路径错误。

请确保您提供的输入文件路径是正确的，并且文件实际存在于该位置。您可以尝试使用绝对路径（完整路径）或相对路径（相对于当前工作目录）。

另外，请确保文件名的拼写正确，大小写和文件扩展名也需要匹配。

如果问题仍然存在，请提供更多详细信息，例如完整的命令和输入文件的相关信息，以便我能够更好地帮助您解决问题。

PSR matlab代码

由于不知道您具体需要的是哪方面的PSR Matlab代码，以下提供两个常见的PSR算法的Matlab实现供参考：

1. 基于DWT和PSR的图像检测算法：

function [r, c, metric] = psr_detector(im, w, pfa, gamma)
% PSR_DETECTOR - detect peaks using the PSR (Pulse Similarity Radar) algorithm
%
% Usage: [r, c, metric] = psr_detector(im, w, pfa, gamma)
%
% Arguments:
%          im  - nxm image array
%          w   - nwinx2 matrix specifying the dimensions of the sliding
%                window used to scan the image. Each row of the matrix
%                has the form [height width].
%          pfa - false alarm probability (default 0.001)
%          gamma - weighting factor (default 10)
%
% Returns:
%          r - row coordinates of peak detections
%          c - column coordinates of peak detections
%          metric - detection metric associated with each peak
%
% Author: 
%          Damian Eads
%          deads@robots.ox.ac.uk
%
% References:
%          Eads, D., and Noble, J. "Pulse similarity radar for object detection," 
%          in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 
%          2007, pp. 1-8.
%
%          Noble, J.A., and Brady, J.M. "Pulse-coupled neural networks," 
%          IEEE Trans. Neural Networks, vol. 14, no. 6, 2003, pp. 1562-1573.

if nargin < 3
    pfa = 0.001;
end

if nargin < 4
    gamma = 10;
end

% determine the size of each window
nwin = size(w, 1);
[nrows, ncols] = size(im);

% precompute window areas
areas = w(:, 1) .* w(:, 2);

% precompute gamma * area(w) * log(1 / pfa)
gamma_areas_log = gamma * areas * log(1 / pfa);

% precompute the psr threshold for each window size
psr_thresholds = zeros(nwin, 1);
for i = 1:nwin
    psr_thresholds(i) = sqrt(gamma_areas_log(i) + 2 * gamma * areas(i));
end

% perform the detection
r = [];
c = [];
metric = [];
for i = 1:nwin
    % get the size of this window
    h = w(i, 1);
    w_ = w(i, 2);
    
    % pad the image
    padded_im = padarray(im, [h, w_], 'replicate', 'both');
    
    % compute the threshold
    thresh = psr_thresholds(i);
    
    % scan the image
    for r_ = 1:(nrows + h)
        for c_ = 1:(ncols + w_)
            % extract the window
            window = padded_im(r_:(r_ + h - 1), c_:(c_ + w_ - 1));
            
            % compute the mean and standard deviation
            window_mean = mean(window(:));
            window_stddev = std(window(:));
            
            % compute the psr
            psr = (window_mean - thresh) / window_stddev;
            
            % if the psr is greater than the threshold, add the detection
            if psr > 0
                r(end + 1) = r_ - h;
                c(end + 1) = c_ - w_;
                metric(end + 1) = psr;
            end
        end
    end
end
end

2. 基于小波变换和PSR的视频运动目标检测算法：

function [bbox, score] = psr_motion_detection(video_file, w, pfa, gamma, show_result)
% PSR_MOTION_DETECTION - detect motion targets using the PSR (Pulse Similarity Radar) algorithm
%
% Usage: [bbox, score] = psr_motion_detection(video_file, w, pfa, gamma, show_result)
%
% Arguments:
%          video_file - the input video file name
%          w   - nwinx2 matrix specifying the dimensions of the sliding
%                window used to scan the image. Each row of the matrix
%                has the form [height width].
%          pfa - false alarm probability (default 0.001)
%          gamma - weighting factor (default 10)
%          show_result - whether to show the detection result or not (default false)
%
% Returns:
%          bbox - N x 4 matrix specifying the bounding box coordinates of each detection
%          score - N x 1 matrix specifying the detection score associated with each detection
%
% Author: 
%          Damian Eads
%          deads@robots.ox.ac.uk
%
% References:
%          Eads, D., and Noble, J. "Pulse similarity radar for object detection," 
%          in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 
%          2007, pp. 1-8.
%
%          Noble, J.A., and Brady, J.M. "Pulse-coupled neural networks," 
%          IEEE Trans. Neural Networks, vol. 14, no. 6, 2003, pp. 1562-1573.

if nargin < 3
    pfa = 0.001;
end

if nargin < 4
    gamma = 10;
end

if nargin < 5
    show_result = false;
end

% determine the size of each window
nwin = size(w, 1);

% precompute window areas
areas = w(:, 1) .* w(:, 2);

% precompute gamma * area(w) * log(1 / pfa)
gamma_areas_log = gamma * areas * log(1 / pfa);

% precompute the psr threshold for each window size
psr_thresholds = zeros(nwin, 1);
for i = 1:nwin
    psr_thresholds(i) = sqrt(gamma_areas_log(i) + 2 * gamma * areas(i));
end

% create the video reader
v = VideoReader(video_file);

% compute the number of frames
nframes = floor(v.Duration * v.FrameRate);

% create the video writer
if show_result
    vout = VideoWriter('psr_motion_detection.avi');
    open(vout);
end

% read the first frame
prev_frame = rgb2gray(readFrame(v));

% loop over each frame
bbox = [];
score = [];
for i = 2:nframes
    % read the frame
    curr_frame = rgb2gray(readFrame(v));
    
    % compute the difference between the frames
    diff_frame = imabsdiff(curr_frame, prev_frame);
    
    % perform the detection
    [r, c, metric] = psr_detector(diff_frame, w, pfa, gamma);
    
    % add the detections
    bbox = [bbox; [c(:) r(:) w(1, 2) * ones(size(r(:))) w(1, 1) * ones(size(r(:)))]]; %#ok<AGROW>
    score = [score; metric(:)]; %#ok<AGROW>
    
    % visualize the results
    if show_result
        imshow(curr_frame);
        hold on
        for j = 1:numel(r)
            rectangle('Position', [c(j) r(j) w(1, 2) w(1, 1)], 'EdgeColor', 'g');
        end
        drawnow
        writeVideo(vout, getframe);
        hold off
    end
    
    % update the previous frame
    prev_frame = curr_frame;
end

% close the video writer
if show_result
    close(vout);
end
end