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ObjectDetection.cpp
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ObjectDetection.cpp
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/**
* @file
* @brief Source file for Object Detection effect class
* @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 "effects/ObjectDetection.h"
#include "effects/Tracker.h"
#include "Exceptions.h"
using namespace std;
using namespace openshot;
/// Blank constructor, useful when using Json to load the effect properties
ObjectDetection::ObjectDetection(std::string clipObDetectDataPath)
{
// Init effect properties
init_effect_details();
// Tries to load the tracker data from protobuf
LoadObjDetectdData(clipObDetectDataPath);
}
// Default constructor
ObjectDetection::ObjectDetection()
{
// Init effect properties
init_effect_details();
}
// Init effect settings
void ObjectDetection::init_effect_details()
{
/// Initialize the values of the EffectInfo struct.
InitEffectInfo();
/// Set the effect info
info.class_name = "Object Detector";
info.name = "Object Detector";
info.description = "Detect objects through the video.";
info.has_audio = false;
info.has_video = true;
}
// This method is required for all derived classes of EffectBase, and returns a
// modified openshot::Frame object
std::shared_ptr<Frame> ObjectDetection::GetFrame(std::shared_ptr<Frame> frame, int64_t frame_number)
{
// Get the frame's image
cv::Mat cv_image = frame->GetImageCV();
// Check if frame isn't NULL
if(cv_image.empty()){
return frame;
}
// Check if track data exists for the requested frame
if (detectionsData.find(frame_number) != detectionsData.end()) {
float fw = cv_image.size().width;
float fh = cv_image.size().height;
DetectionData detections = detectionsData[frame_number];
for(int i = 0; i<detections.boxes.size(); i++){
cv::Rect_<float> bb_nrml = detections.boxes.at(i);
cv::Rect2d box((int)(bb_nrml.x*fw),
(int)(bb_nrml.y*fh),
(int)(bb_nrml.width*fw),
(int)(bb_nrml.height*fh));
drawPred(detections.classIds.at(i), detections.confidences.at(i),
box, cv_image);
}
}
// Set image with drawn box to frame
// If the input image is NULL or doesn't have tracking data, it's returned as it came
frame->SetImageCV(cv_image);
return frame;
}
void ObjectDetection::drawPred(int classId, float conf, cv::Rect2d box, cv::Mat& frame)
{
//Draw a rectangle displaying the bounding box
cv::rectangle(frame, box, classesColor[classId], 2);
//Get the label for the class name and its confidence
std::string label = cv::format("%.2f", conf);
if (!classNames.empty())
{
CV_Assert(classId < (int)classNames.size());
label = classNames[classId] + ":" + label;
}
//Display the label at the top of the bounding box
int baseLine;
cv::Size labelSize = cv::getTextSize(label, cv::FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseLine);
double left = box.x;
double top = std::max((int)box.y, labelSize.height);
cv::rectangle(frame, cv::Point(left, top - round(1.025*labelSize.height)), cv::Point(left + round(1.025*labelSize.width), top + baseLine), classesColor[classId], cv::FILLED);
putText(frame, label, cv::Point(left+1, top), cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0,0,0),1);
}
// Load protobuf data file
bool ObjectDetection::LoadObjDetectdData(std::string inputFilePath){
// Create tracker message
pb_objdetect::ObjDetect objMessage;
{
// Read the existing tracker message.
std::fstream input(inputFilePath, std::ios::in | std::ios::binary);
if (!objMessage.ParseFromIstream(&input)) {
std::cerr << "Failed to parse protobuf message." << std::endl;
return false;
}
}
// Make sure classNames and detectionsData are empty
classNames.clear();
detectionsData.clear();
// Seed to generate same random numbers
std::srand(1);
// Get all classes names and assign a color to them
for(int i = 0; i < objMessage.classnames_size(); i++){
classNames.push_back(objMessage.classnames(i));
classesColor.push_back(cv::Scalar(std::rand()%205 + 50, std::rand()%205 + 50, std::rand()%205 + 50));
}
// Iterate over all frames of the saved message
for (size_t i = 0; i < objMessage.frame_size(); i++) {
// Create protobuf message reader
const pb_objdetect::Frame& pbFrameData = objMessage.frame(i);
// Get frame Id
size_t id = pbFrameData.id();
// Load bounding box data
const google::protobuf::RepeatedPtrField<pb_objdetect::Frame_Box > &pBox = pbFrameData.bounding_box();
// Construct data vectors related to detections in the current frame
std::vector<int> classIds;
std::vector<float> confidences;
std::vector<cv::Rect_<float>> boxes;
for(int i = 0; i < pbFrameData.bounding_box_size(); i++){
// Get bounding box coordinates
float x = pBox.Get(i).x();
float y = pBox.Get(i).y();
float w = pBox.Get(i).w();
float h = pBox.Get(i).h();
// Get class Id (which will be assign to a class name)
int classId = pBox.Get(i).classid();
// Get prediction confidence
float confidence = pBox.Get(i).confidence();
// Create OpenCV rectangle with the bouding box info
cv::Rect_<float> box(x, y, w, h);
// Push back data into vectors
boxes.push_back(box);
classIds.push_back(classId);
confidences.push_back(confidence);
}
// Assign data to object detector map
detectionsData[id] = DetectionData(classIds, confidences, boxes, id);
}
// Delete all global objects allocated by libprotobuf.
google::protobuf::ShutdownProtobufLibrary();
return true;
}
// Get tracker info for the desired frame
DetectionData ObjectDetection::GetTrackedData(size_t frameId){
// Check if the tracker info for the requested frame exists
if ( detectionsData.find(frameId) == detectionsData.end() ) {
return DetectionData();
} else {
return detectionsData[frameId];
}
}
// Generate JSON string of this object
std::string ObjectDetection::Json() const {
// Return formatted string
return JsonValue().toStyledString();
}
// Generate Json::Value for this object
Json::Value ObjectDetection::JsonValue() const {
// Create root json object
Json::Value root = EffectBase::JsonValue(); // get parent properties
root["type"] = info.class_name;
root["protobuf_data_path"] = protobuf_data_path;
// return JsonValue
return root;
}
// Load JSON string into this object
void ObjectDetection::SetJson(const std::string value) {
// Parse JSON string into JSON objects
try
{
const Json::Value root = openshot::stringToJson(value);
// Set all values that match
SetJsonValue(root);
}
catch (const std::exception& e)
{
// Error parsing JSON (or missing keys)
throw InvalidJSON("JSON is invalid (missing keys or invalid data types)");
}
}
// Load Json::Value into this object
void ObjectDetection::SetJsonValue(const Json::Value root) {
// Set parent data
EffectBase::SetJsonValue(root);
// Set data from Json (if key is found)
if (!root["protobuf_data_path"].isNull()){
protobuf_data_path = (root["protobuf_data_path"].asString());
if(!LoadObjDetectdData(protobuf_data_path)){
std::cout<<"Invalid protobuf data path";
protobuf_data_path = "";
}
}
}
// Get all properties for a specific frame
std::string ObjectDetection::PropertiesJSON(int64_t requested_frame) const {
// Generate JSON properties list
Json::Value root;
root["id"] = add_property_json("ID", 0.0, "string", Id(), NULL, -1, -1, true, requested_frame);
root["position"] = add_property_json("Position", Position(), "float", "", NULL, 0, 1000 * 60 * 30, false, requested_frame);
root["layer"] = add_property_json("Track", Layer(), "int", "", NULL, 0, 20, false, requested_frame);
root["start"] = add_property_json("Start", Start(), "float", "", NULL, 0, 1000 * 60 * 30, false, requested_frame);
root["end"] = add_property_json("End", End(), "float", "", NULL, 0, 1000 * 60 * 30, false, requested_frame);
root["duration"] = add_property_json("Duration", Duration(), "float", "", NULL, 0, 1000 * 60 * 30, true, requested_frame);
// Return formatted string
return root.toStyledString();
}