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* reuse-managed license/copyright headers reuse is a tool for compliance with the REUSE recommendations. See <https://reuse.software/> for more information, and <https://reuse.readthedocs.io/> for the online documentation. * Set jsoncpp license * Add MIT license for Decklink sources * Explicitly license examples/ - Add headers to source files - Change blanket licensing in .reuse/dep5 to only cover binary media - Import CC-BY-3.0 license and assign to sintel_trailer
284 lines
9.8 KiB
C++
284 lines
9.8 KiB
C++
/**
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* @file
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* @brief Source file for Example Executable (example app for libopenshot)
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* @author Jonathan Thomas <jonathan@openshot.org>
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*
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* @ref License
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*/
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// Copyright (c) 2008-2019 OpenShot Studios, LLC
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//
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// SPDX-License-Identifier: LGPL-3.0-or-later
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#include <fstream>
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#include <iostream>
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#include <memory>
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#include "CVTracker.h"
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#include "CVStabilization.h"
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#include "CVObjectDetection.h"
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#include "Clip.h"
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#include "EffectBase.h"
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#include "EffectInfo.h"
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#include "Frame.h"
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#include "CrashHandler.h"
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using namespace openshot;
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using namespace std;
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/*
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The following methods are just for getting JSON info to the pre-processing effects
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*/
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string jsonFormat(string key, string value, string type="string"); // Format variables to the needed JSON format
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string trackerJson(cv::Rect2d r, bool onlyProtoPath); // Set variable values for tracker effect
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string stabilizerJson(bool onlyProtoPath); // Set variable values for stabilizer effect
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string objectDetectionJson(bool onlyProtoPath); // Set variable values for object detector effect
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/*
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*/
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// Show the pre-processed clip on the screen
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void displayClip(openshot::Clip &r9){
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// Opencv display window
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cv::namedWindow("Display Image", cv::WINDOW_NORMAL );
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// Get video lenght
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int videoLenght = r9.Reader()->info.video_length;
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// Loop through the clip and show it with the effects, if any
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for (long int frame = 0; frame < videoLenght; frame++)
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{
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int frame_number = frame;
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// Get the frame
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std::shared_ptr<openshot::Frame> f = r9.GetFrame(frame_number);
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// Grab OpenCV::Mat image
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cv::Mat cvimage = f->GetImageCV();
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// Display the frame
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cv::imshow("Display Image", cvimage);
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// Press ESC on keyboard to exit
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char c=(char)cv::waitKey(25);
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if(c==27)
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break;
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}
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// Destroy all remaining windows
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cv::destroyAllWindows();
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}
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int main(int argc, char* argv[]) {
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// Set pre-processing effects
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bool TRACK_DATA = true;
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bool SMOOTH_VIDEO = false;
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bool OBJECT_DETECTION_DATA = false;
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// Get media path
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std::stringstream path;
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path << TEST_MEDIA_PATH << ((OBJECT_DETECTION_DATA) ? "run.mp4" : "test.avi");
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// run.mp4 --> Used for object detector
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// test.avi --> Used for tracker and stabilizer
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// Thread controller just for the pre-processing constructors, it won't be used
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ProcessingController processingController;
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// Open clip
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openshot::Clip r9(path.str());
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r9.Open();
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// Apply tracking effect on the clip
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if(TRACK_DATA){
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// Take the bounding box coordinates
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cv::Mat roi = r9.GetFrame(0)->GetImageCV();
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cv::Rect2d r = cv::selectROI(roi);
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cv::destroyAllWindows();
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// Create a tracker object by passing a JSON string and a thread controller, this last one won't be used
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// JSON info: path to save the tracked data, type of tracker and bbox coordinates
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CVTracker tracker(trackerJson(r, false), processingController);
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// Start the tracking
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tracker.trackClip(r9, 0, 0, true);
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// Save the tracked data
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tracker.SaveTrackedData();
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// Create a tracker effect
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EffectBase* e = EffectInfo().CreateEffect("Tracker");
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// Pass a JSON string with the saved tracked data
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// The effect will read and save the tracking in a map::<frame,data_struct>
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e->SetJson(trackerJson(r, true));
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// Add the effect to the clip
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r9.AddEffect(e);
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}
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// Apply stabilizer effect on the clip
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if(SMOOTH_VIDEO){
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// Create a stabilizer object by passing a JSON string and a thread controller, this last one won't be used
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// JSON info: path to save the stabilized data and smoothing window value
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CVStabilization stabilizer(stabilizerJson(false), processingController);
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// Start the stabilization
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stabilizer.stabilizeClip(r9, 0, 100, true);
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// Save the stabilization data
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stabilizer.SaveStabilizedData();
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// Create a stabilizer effect
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EffectBase* e = EffectInfo().CreateEffect("Stabilizer");
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// Pass a JSON string with the saved stabilized data
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// The effect will read and save the stabilization in a map::<frame,data_struct>
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e->SetJson(stabilizerJson(true));
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// Add the effect to the clip
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r9.AddEffect(e);
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}
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// Apply object detection effect on the clip
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if(OBJECT_DETECTION_DATA){
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// Create a object detection object by passing a JSON string and a thread controller, this last one won't be used
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// JSON info: path to save the detection data, processing devicee, model weights, model configuration and class names
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CVObjectDetection objectDetection(objectDetectionJson(false), processingController);
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// Start the object detection
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objectDetection.detectObjectsClip(r9, 0, 100, true);
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// Save the object detection data
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objectDetection.SaveObjDetectedData();
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// Create a object detector effect
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EffectBase* e = EffectInfo().CreateEffect("Object Detector");
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// Pass a JSON string with the saved detections data
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// The effect will read and save the detections in a map::<frame,data_struct>
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e->SetJson(objectDetectionJson(true));
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// Add the effect to the clip
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r9.AddEffect(e);
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}
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// Show the pre-processed clip on the screen
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displayClip(r9);
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// Close timeline
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r9.Close();
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std::cout << "Completed successfully!" << std::endl;
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return 0;
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}
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/*
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The following methods are just for getting JSON info to the pre-processing effects
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*/
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string jsonFormat(string key, string value, string type){
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stringstream jsonFormatMessage;
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jsonFormatMessage << ( "\"" + key + "\": " );
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if(type == "string")
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jsonFormatMessage << ( "\"" + value + "\"" );
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if(type == "rstring")
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jsonFormatMessage << value;
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if(type == "int")
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jsonFormatMessage << stoi(value);
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if(type == "float")
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jsonFormatMessage << (float)stof(value);
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if(type == "double")
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jsonFormatMessage << (double)stof(value);
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if (type == "bool")
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jsonFormatMessage << ((value == "true" || value == "1") ? "true" : "false");
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return jsonFormatMessage.str();
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}
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// Return JSON string for the tracker effect
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string trackerJson(cv::Rect2d r, bool onlyProtoPath){
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// Define path to save tracked data
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string protobufDataPath = "kcf_tracker.data";
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// Set the tracker
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string tracker = "KCF";
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// Construct all the composition of the JSON string
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string protobuf_data_path = jsonFormat("protobuf_data_path", protobufDataPath);
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string trackerType = jsonFormat("tracker-type", tracker);
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string bboxCoords = jsonFormat(
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"region",
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"{" + jsonFormat("x", to_string(r.x), "int") +
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"," + jsonFormat("y", to_string(r.y), "int") +
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"," + jsonFormat("width", to_string(r.width), "int") +
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"," + jsonFormat("height", to_string(r.height), "int") +
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"," + jsonFormat("first-frame", to_string(0), "int") +
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"}",
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"rstring");
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// Return only the the protobuf path in JSON format
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if(onlyProtoPath)
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return "{" + protobuf_data_path + "}";
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// Return all the parameters for the pre-processing effect
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else
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return "{" + protobuf_data_path + "," + trackerType + "," + bboxCoords + "}";
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}
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// Return JSON string for the stabilizer effect
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string stabilizerJson(bool onlyProtoPath){
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// Define path to save stabilized data
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string protobufDataPath = "example_stabilizer.data";
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// Set smoothing window value
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string smoothingWindow = "30";
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// Construct all the composition of the JSON string
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string protobuf_data_path = jsonFormat("protobuf_data_path", protobufDataPath);
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string smoothing_window = jsonFormat("smoothing_window", smoothingWindow, "int");
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// Return only the the protobuf path in JSON format
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if(onlyProtoPath)
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return "{" + protobuf_data_path + "}";
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// Return all the parameters for the pre-processing effect
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else
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return "{" + protobuf_data_path + "," + smoothing_window + "}";
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}
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string objectDetectionJson(bool onlyProtoPath){
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// Define path to save object detection data
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string protobufDataPath = "example_object_detection.data";
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// Define processing device
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string processingDevice = "GPU";
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// Set path to model configuration file
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string modelConfiguration = "yolov3.cfg";
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// Set path to model weights
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string modelWeights = "yolov3.weights";
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// Set path to class names file
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string classesFile = "obj.names";
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// Construct all the composition of the JSON string
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string protobuf_data_path = jsonFormat("protobuf_data_path", protobufDataPath);
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string processing_device = jsonFormat("processing_device", processingDevice);
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string model_configuration = jsonFormat("model_configuration", modelConfiguration);
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string model_weights = jsonFormat("model_weights", modelWeights);
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string classes_file = jsonFormat("classes_file", classesFile);
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// Return only the the protobuf path in JSON format
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if(onlyProtoPath)
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return "{" + protobuf_data_path + "}";
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else
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return "{" + protobuf_data_path + "," + processing_device + "," + model_configuration + ","
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+ model_weights + "," + classes_file + "}";
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}
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