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Example_opencv.cpp
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Example_opencv.cpp
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/**
* @file
* @brief Source file for Example Executable (example app for libopenshot)
* @author Jonathan Thomas <jonathan@openshot.org>
*
* @ref License
*/
/* LICENSE
*
* Copyright (c) 2008-2019 OpenShot Studios, LLC
* <http://www.openshotstudios.com/>. This file is part of
* OpenShot Library (libopenshot), an open-source project dedicated to
* delivering high quality video editing and animation solutions to the
* world. For more information visit <http://www.openshot.org/>.
*
* OpenShot Library (libopenshot) is free software: you can redistribute it
* and/or modify it under the terms of the GNU Lesser General Public License
* as published by the Free Software Foundation, either version 3 of the
* License, or (at your option) any later version.
*
* OpenShot Library (libopenshot) 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 Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public License
* along with OpenShot Library. If not, see <http://www.gnu.org/licenses/>.
*/
#include <fstream>
#include <iostream>
#include <memory>
#include "../../include/CVTracker.h"
#include "../../include/CVStabilization.h"
#include "../../include/CVObjectDetection.h"
#include "../../include/OpenShot.h"
#include "../../include/CrashHandler.h"
using namespace openshot;
using namespace std;
/*
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
The following methods are just for getting JSON info to the pre-processing effects
*/
string jsonFormat(string key, string value, string type="string"); // Format variables to the needed JSON format
string trackerJson(cv::Rect2d r, bool onlyProtoPath); // Set variable values for tracker effect
string stabilizerJson(bool onlyProtoPath); // Set variable values for stabilizer effect
string objectDetectionJson(bool onlyProtoPath); // Set variable values for object detector effect
/*
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
*/
// Show the pre-processed clip on the screen
void displayClip(openshot::Clip &r9){
// Opencv display window
cv::namedWindow("Display Image", cv::WINDOW_NORMAL );
// Get video lenght
int videoLenght = r9.Reader()->info.video_length;
// Loop through the clip and show it with the effects, if any
for (long int frame = 0; frame < videoLenght; frame++)
{
int frame_number = frame;
// Get the frame
std::shared_ptr<openshot::Frame> f = r9.GetFrame(frame_number);
// Grab OpenCV::Mat image
cv::Mat cvimage = f->GetImageCV();
// Display the frame
cv::imshow("Display Image", cvimage);
// Press ESC on keyboard to exit
char c=(char)cv::waitKey(25);
if(c==27)
break;
}
// Destroy all remaining windows
cv::destroyAllWindows();
}
int main(int argc, char* argv[]) {
// Set pre-processing effects
bool TRACK_DATA = true;
bool SMOOTH_VIDEO = false;
bool OBJECT_DETECTION_DATA = false;
// Get media path
std::stringstream path;
path << TEST_MEDIA_PATH << ((OBJECT_DETECTION_DATA) ? "run.mp4" : "test.avi");
// run.mp4 --> Used for object detector
// test.avi --> Used for tracker and stabilizer
// Thread controller just for the pre-processing constructors, it won't be used
ProcessingController processingController;
// Open clip
openshot::Clip r9(path.str());
r9.Open();
// Apply tracking effect on the clip
if(TRACK_DATA){
// Take the bounding box coordinates
cv::Mat roi = r9.GetFrame(0)->GetImageCV();
cv::Rect2d r = cv::selectROI(roi);
cv::destroyAllWindows();
// Create a tracker object by passing a JSON string and a thread controller, this last one won't be used
// JSON info: path to save the tracked data, type of tracker and bbox coordinates
CVTracker tracker(trackerJson(r, false), processingController);
// Start the tracking
tracker.trackClip(r9, 0, 100, true);
// Save the tracked data
tracker.SaveTrackedData();
// Create a tracker effect
EffectBase* e = EffectInfo().CreateEffect("Tracker");
// Pass a JSON string with the saved tracked data
// The effect will read and save the tracking in a map::<frame,data_struct>
e->SetJson(trackerJson(r, true));
// Add the effect to the clip
r9.AddEffect(e);
}
// Apply stabilizer effect on the clip
if(SMOOTH_VIDEO){
// Create a stabilizer object by passing a JSON string and a thread controller, this last one won't be used
// JSON info: path to save the stabilized data and smoothing window value
CVStabilization stabilizer(stabilizerJson(false), processingController);
// Start the stabilization
stabilizer.stabilizeClip(r9, 0, 100, true);
// Save the stabilization data
stabilizer.SaveStabilizedData();
// Create a stabilizer effect
EffectBase* e = EffectInfo().CreateEffect("Stabilizer");
// Pass a JSON string with the saved stabilized data
// The effect will read and save the stabilization in a map::<frame,data_struct>
e->SetJson(stabilizerJson(true));
// Add the effect to the clip
r9.AddEffect(e);
}
// Apply object detection effect on the clip
if(OBJECT_DETECTION_DATA){
// Create a object detection object by passing a JSON string and a thread controller, this last one won't be used
// JSON info: path to save the detection data, processing devicee, model weights, model configuration and class names
CVObjectDetection objectDetection(objectDetectionJson(false), processingController);
// Start the object detection
objectDetection.detectObjectsClip(r9, 0, 100, true);
// Save the object detection data
objectDetection.SaveObjDetectedData();
// Create a object detector effect
EffectBase* e = EffectInfo().CreateEffect("Object Detector");
// Pass a JSON string with the saved detections data
// The effect will read and save the detections in a map::<frame,data_struct>
e->SetJson(objectDetectionJson(true));
// Add the effect to the clip
r9.AddEffect(e);
}
// Show the pre-processed clip on the screen
displayClip(r9);
// Close timeline
r9.Close();
std::cout << "Completed successfully!" << std::endl;
return 0;
}
/*
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
The following methods are just for getting JSON info to the pre-processing effects
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
*/
string jsonFormat(string key, string value, string type){
stringstream jsonFormatMessage;
jsonFormatMessage << ( "\"" + key + "\": " );
if(type == "string")
jsonFormatMessage << ( "\"" + value + "\"" );
if(type == "rstring")
jsonFormatMessage << value;
if(type == "int")
jsonFormatMessage << stoi(value);
if(type == "float")
jsonFormatMessage << (float)stof(value);
if(type == "double")
jsonFormatMessage << (double)stof(value);
if (type == "bool")
jsonFormatMessage << ((value == "true" || value == "1") ? "true" : "false");
return jsonFormatMessage.str();
}
// Return JSON string for the tracker effect
string trackerJson(cv::Rect2d r, bool onlyProtoPath){
// Define path to save tracked data
string protobufDataPath = "kcf_tracker.data";
// Set the tracker
string tracker = "KCF";
// Construct all the composition of the JSON string
string protobuf_data_path = jsonFormat("protobuf_data_path", protobufDataPath);
string trackerType = jsonFormat("tracker_type", tracker);
string bboxCoords = jsonFormat(
"bbox",
"{" + jsonFormat("x", to_string(r.x), "int") +
"," + jsonFormat("y", to_string(r.y), "int") +
"," + jsonFormat("w", to_string(r.width), "int") +
"," + jsonFormat("h", to_string(r.height), "int") +
"}",
"rstring");
// Return only the the protobuf path in JSON format
if(onlyProtoPath)
return "{" + protobuf_data_path + "}";
// Return all the parameters for the pre-processing effect
else
return "{" + protobuf_data_path + "," + trackerType + "," + bboxCoords + "}";
}
// Return JSON string for the stabilizer effect
string stabilizerJson(bool onlyProtoPath){
// Define path to save stabilized data
string protobufDataPath = "example_stabilizer.data";
// Set smoothing window value
string smoothingWindow = "30";
// Construct all the composition of the JSON string
string protobuf_data_path = jsonFormat("protobuf_data_path", protobufDataPath);
string smoothing_window = jsonFormat("smoothing_window", smoothingWindow, "int");
// Return only the the protobuf path in JSON format
if(onlyProtoPath)
return "{" + protobuf_data_path + "}";
// Return all the parameters for the pre-processing effect
else
return "{" + protobuf_data_path + "," + smoothing_window + "}";
}
string objectDetectionJson(bool onlyProtoPath){
// Define path to save object detection data
string protobufDataPath = "example_object_detection.data";
// Define processing device
string processingDevice = "GPU";
// Set path to model configuration file
string modelConfiguration = "yolov3.cfg";
// Set path to model weights
string modelWeights = "yolov3.weights";
// Set path to class names file
string classesFile = "obj.names";
// Construct all the composition of the JSON string
string protobuf_data_path = jsonFormat("protobuf_data_path", protobufDataPath);
string processing_device = jsonFormat("processing_device", processingDevice);
string model_configuration = jsonFormat("model_configuration", modelConfiguration);
string model_weights = jsonFormat("model_weights", modelWeights);
string classes_file = jsonFormat("classes_file", classesFile);
// Return only the the protobuf path in JSON format
if(onlyProtoPath)
return "{" + protobuf_data_path + "}";
else
return "{" + protobuf_data_path + "," + processing_device + "," + model_configuration + ","
+ model_weights + "," + classes_file + "}";
}