SpeedupVideo.m

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%%   This file is part of SemanticFastForward_JVCI.
%
%    SemanticFastForward_JVCI is free software: you can redistribute it and/or modify
%    it under the terms of the GNU General Public License as published by
%    the Free Software Foundation, either version 3 of the License, or
%    (at your option) any later version.
%
%    SemanticFastForward_JVCI is distributed in the hope that it will be useful,
%    but WITHOUT ANY WARRANTY; without even the implied warranty of
%    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
%    GNU General Public License for more details.
%
%    You should have received a copy of the GNU General Public License
%    along with SemanticFastForward_JVCI.  If not, see <http://www.gnu.org/licenses/>.
%
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% Create a fast forward video based on the arguments
%
% video_dir -> Video Directory
% experiment -> Experiment Name
% semantic_extractor -> The extractor (face, pedestrian, coolnet,...)
%
% Other arguments (see function parser)
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function SpeedupVideo(video_dir, experiment, semantic_extractor, varargin)
    close all
    warning ('off', 'images:initSize:adjustingMag');
    addpath(genpath(pwd));

    %% Parsing input parameters
    p = inputParser;

    validSemanticExtractor = {'none', 'face', 'pedestrian', 'coolnet'};
    checkSemanticExtractor = @(x) any(validatestring(x,validSemanticExtractor));
    addRequired(p,'semantic_extractor', checkSemanticExtractor);

    addOptional(p, 'SaveGeneralResults', true, @islogical);
    addOptional(p, 'ExportOutputVideo', true, @islogical);
    addOptional(p, 'ShakinessWeights', [0, 0], @isrow);
    addOptional(p, 'VelocityWeights', [0, 0], @isrow);
    addOptional(p, 'AppearanceWeights', [0, 0], @isrow);
    addOptional(p, 'SemanticWeights', [0, 0], @isrow);
    addOptional(p, 'ForwardnessWeights', [0, 0], @isrow);
    addOptional(p, 'HigherOrderWeights', [0, 0], @isrow);
    addOptional(p, 'Speedup', 10, @isnumeric);

    validAlgorithm = {'Naive', 'NaiveSemantic', 'EgoSampling', 'FFSE'};
    checkAlgorithm = @(x) any(validatestring(x,validAlgorithm));
    addOptional(p, 'Algorithm', 'FFSE', checkAlgorithm); %'Naive', 'NaiveSemantic', 'EgoSampling', 'FFSE'

    parse(p, semantic_extractor, varargin{:});

    %% Assignments
    save_general_results_to_file = p.Results.SaveGeneralResults;
    skip_video_output = ~p.Results.ExportOutputVideo;
    shakiness_weights = p.Results.ShakinessWeights;
    velocity_weights = p.Results.VelocityWeights;
    appearance_weights = p.Results.AppearanceWeights;
    semantic_weights = p.Results.SemanticWeights;
    forwardness_weights = p.Results.ForwardnessWeights;
    high_order_weights = p.Results.HigherOrderWeights;
    required_speedup = p.Results.Speedup;
    algorithm = p.Results.Algorithm;

    %% Defining the optimization characteristic
    optimize = strcmp(algorithm, 'FFSE') && (isempty(nonzeros(shakiness_weights)) && isempty(nonzeros(velocity_weights)) &&...
        isempty(nonzeros(appearance_weights)) && isempty(nonzeros(semantic_weights)) &&...
        isempty(nonzeros(forwardness_weights)) && isempty(nonzeros(high_order_weights)));

    %% Getting the experiment details
    fprintf('%sGetting ''%s'' details...\n', log_line_prefix, experiment);
    cfg = SemanticSequenceLibrary.GetFFExperimentDetails(video_dir, experiment, algorithm, required_speedup, skip_video_output);

    startInd = cfg.get('startInd');
    endInd = cfg.get('endInd');

    [~, fname, ~] = fileparts(cfg.get('inputVideoFileName'));

    % Load the video .mat file
    fpstereo = [video_dir '/' fname 'fpstereo.mat'];
    if ~exist(fpstereo, 'file')
        fprintf('%sPreprocess file not found...\n', log_line_prefix);
        optical_flow_csv = [video_dir '/' fname '.csv'];
        if exist(optical_flow_csv, 'file') == 0
            fprintf('%sOptical Flow CSV file not found...\n', log_line_prefix);
            error('Please run Vid2OpticalFlowCSV first!');
        end
        fprintf('%sPreprocessing optical flow data...\n', log_line_prefix);
        Util.PrepreocessSequences(cfg.get('inputVideoFileName'), '');
        fprintf('%sDone preprocessing optical flow data...\n', log_line_prefix);
    end

    sd = Util.LoadVidDataFromMat(cfg.get('inputVideoFileName'),'fpstereo','returnonly');

    % End index treatment
    if endInd > size(sd.CDC_Raw_X,1) + sd.StartFrame-1
        endInd = size(sd.CDC_Raw_X,1) + sd.StartFrame-1;
    end

    if save_general_results_to_file
        general_results = [video_dir '/out/' fname '_GeneralResults.csv'];

        if ( exist(general_results, 'file') == 2 )
            results_csv = fopen(general_results, 'a');
        else
            if ~exist([video_dir '/out/'], 'dir')
                mkdir(video_dir, 'out')
            end
            [results_csv, msg] = fopen(general_results, 'a');
            if (results_csv < 0)
                error('Could not open/create file.\nReason: %s', msg);
            end
            fprintf(results_csv, 'Experiment ID,Algorithm,Required Speedup,Achieved Speedup,Alphas,Betas,Gammas,Etas,Deltas,Zetas,# Selected Frames,# Faces in Selected Frames,Avg. Skip Frames,Median Skip Frames,Faces Value,Jitter,Instability\n');
        end
    end

    %% Satisfying the semantic requirements
    semantic_filename = [video_dir '/' fname '_' semantic_extractor '_extracted.mat'];

    fprintf('%sAttaching the semantic extraction information...\n', log_line_prefix);
    if exist(semantic_filename, 'file')
        load(semantic_filename);
        SemanticData = Rects;
        clear Rects;
        clear total_values;
    else
        error('Please, run ExtractAndSave with the extractor ''%s'' to extract the semantic information first!', semantic_extractor);
    end

    if strcmp(algorithm, 'FFSE')%Only our algorithm requires speedup calculation
        fprintf('%sCalculating speedup rates...\n', log_line_prefix);

        [Speedups, SemanticRanges, RangesAndSpeedups, err] = CalculateSpeedupRates(semantic_filename, required_speedup,...
            'MultipleThresholds', cfg.get('UseMultipleSemanticThresholds'), 'InputRange', [startInd endInd]);

        [RangesAndSpeedups] = AddNonSemanticRanges(RangesAndSpeedups, Speedups, startInd, endInd, 50);

        fprintf('-----------------------------------------------------------------------------------------------\n');
        fprintf('%sChosen ranges and speedups:\n', log_line_prefix);
        for i=1:size(RangesAndSpeedups,2)
            fprintf('%sRange[%d-%d]\t@ (%dx)\t-- Length(%d)\t-- Semantic? %d\n', log_line_prefix,...
                RangesAndSpeedups(1,i), RangesAndSpeedups(2,i),RangesAndSpeedups(3,i),...
                RangesAndSpeedups(2,i)-RangesAndSpeedups(1,i),RangesAndSpeedups(4,i));
        end
        fprintf('-----------------------------------------------------------------------------------------------\n');
        fprintf('\n');

        cfg.set('Speedups', Speedups);
        cfg.set('SemanticRanges', SemanticRanges);
        cfg.set('RangesAndSpeedups', RangesAndSpeedups);
    else
        RangesAndSpeedups = [startInd; endInd; required_speedup; 0];
        cfg.set('RangesAndSpeedups', RangesAndSpeedups);
    end

    %% More assignments
    cfg.set('ShakinessTermWeight', [shakiness_weights(1), shakiness_weights(2)]);
    cfg.set('VelocityTermWeight', [velocity_weights(1), velocity_weights(2)]);
    cfg.set('AppearanceTermWeight', [appearance_weights(1), appearance_weights(2)]);
    cfg.set('SemanticTermWeight', [semantic_weights(1), semantic_weights(2)]);
    cfg.set('ForwardnessTermWeight', [forwardness_weights(1), forwardness_weights(2)]);
    cfg.set('HighOrderTermWeight', [high_order_weights(1), high_order_weights(2)]);

    se = SemanticFastForward(sd,cfg, SemanticData, strcmp(algorithm, 'FFSE'),optimize);

    fprintf('%sRunning Experiment...\n', log_line_prefix);
    se.run();

    shakiness_weights = cfg.get('ShakinessTermWeight');
    velocity_weights = cfg.get('VelocityTermWeight');
    appearance_weights = cfg.get('AppearanceTermWeight');
    semantic_weights = cfg.get('SemanticTermWeight');
    forwardness_weights = cfg.get('ForwardnessTermWeight');
    high_order_weights = cfg.get('HighOrderTermWeight');

    if save_general_results_to_file
        if cfg.get('UseHigherOrder')
            fprintf(results_csv, '%d,%s,%d,%.3f,[%.3f %.3f],[%.3f %.3f],[%.3f %.3f],[%.3f %.3f],[%.3f %.3f],[%.3f %.3f], %d, %d, %.3f, %.3f, %.4f, %.4f, %.4f\n',...
                cfg.get('ID'),algorithm,required_speedup,se.ResultsMetaData.achieved_speedup,shakiness_weights(1),shakiness_weights(2),velocity_weights(1),velocity_weights(2),appearance_weights(1),appearance_weights(2),...
                semantic_weights(1),semantic_weights(2),forwardness_weights(1),forwardness_weights(2),high_order_weights(1),high_order_weights(2),...
                size(se.ResultsMetaData.frames,1), se.ResultsMetaData.total_semantic_in_frames, se.ResultsMetaData.avarage_skip,...
                se.ResultsMetaData.median_skip, se.ResultsMetaData.semantic_value, se.ResultsMetaData.jitter, se.ResultsMetaData.instability);
        else
            fprintf(results_csv, '%d,%s,%d,%.3f,[%.3f %.3f],[%.3f %.3f],[%.3f %.3f],[%.3f %.3f],[x x],[x x],%d, %d, %.3f, %.3f, %.4f, %.4f, %.4f\n',...
                cfg.get('ID'),algorithm,required_speedup,se.ResultsMetaData.achieved_speedup,shakiness_weights(1),shakiness_weights(2),velocity_weights(1),velocity_weights(2),appearance_weights(1),appearance_weights(2),...
                semantic_weights(1),semantic_weights(2), size(se.ResultsMetaData.frames,1), se.ResultsMetaData.total_semantic_in_frames, se.ResultsMetaData.avarage_skip,...
                se.ResultsMetaData.median_skip, se.ResultsMetaData.semantic_value, se.ResultsMetaData.jitter, se.ResultsMetaData.instability);
        end
    end

    % Creating semantic cost csv for stabilizer
    video_speedup = cfg.get('FastForwardSkipRatio');
    cost_path = [video_dir '/' experiment '_SemanticCosts_' num2str(video_speedup) 'x.csv'];
    if exist(cost_path, 'file') == 0
        csvwrite(cost_path, startInd);
        dlmwrite(cost_path, se.Semantic_cost, 'delimiter' , ',' , '-append');
    end

    fprintf('%sDone! Experiment #%d finished\n',log_line_prefix,cfg.get('ID'));

    if save_general_results_to_file
        fclose(results_csv);
    end
end