073a6efa0198596d8e03c488ed594090ae5dd7ec
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28 #include <signal.h>
29 #include <iostream>
30 #include <iomanip>
31 #include <fstream>
32 #include <cassert>
33 #include <string>
34 #include <functional>
35 #include <algorithm>
36 #include <time.h>
37 #include <unistd.h>
39 #include <queue>
40 #include <vector>
41 #include <cstdio>
42 #include <chrono>
44 #include "executor.h"
45 #include "execution_object.h"
46 #include "execution_object_pipeline.h"
47 #include "configuration.h"
48 #include "../segmentation/object_classes.h"
49 #include "../common/utils.h"
50 #include "../common/video_utils.h"
52 using namespace std;
53 using namespace tidl;
54 using namespace cv;
57 #define NUM_VIDEO_FRAMES 100
58 #define DEFAULT_CONFIG "jdetnet"
59 #define DEFAULT_INPUT "../test/testvecs/input/preproc_0_768x320.y"
60 #define DEFAULT_INPUT_FRAMES (1)
62 object_class_table_t *object_class_table;
63 uint32_t orig_width;
64 uint32_t orig_height;
67 bool RunConfiguration(const cmdline_opts_t& opts);
68 Executor* CreateExecutor(DeviceType dt, int num, const Configuration& c,
69 int layers_group_id);
70 bool ReadFrame(ExecutionObjectPipeline& eop, int frame_idx,
71 const Configuration& c, const cmdline_opts_t& opts,
72 VideoCapture &cap);
73 bool WriteFrameOutput(const ExecutionObjectPipeline& eop,
74 const Configuration& c, const cmdline_opts_t& opts);
75 static void DisplayHelp();
78 int main(int argc, char *argv[])
79 {
80 // Catch ctrl-c to ensure a clean exit
81 signal(SIGABRT, exit);
82 signal(SIGTERM, exit);
84 // If there are no devices capable of offloading TIDL on the SoC, exit
85 uint32_t num_eves = Executor::GetNumDevices(DeviceType::EVE);
86 uint32_t num_dsps = Executor::GetNumDevices(DeviceType::DSP);
87 if (num_eves == 0 || num_dsps == 0)
88 {
89 cout << "ssd_multibox requires both EVE and DSP for execution." << endl;
90 return EXIT_SUCCESS;
91 }
93 // Process arguments
94 cmdline_opts_t opts;
95 opts.config = DEFAULT_CONFIG;
96 opts.num_eves = 1;
97 opts.num_dsps = 1;
98 if (! ProcessArgs(argc, argv, opts))
99 {
100 DisplayHelp();
101 exit(EXIT_SUCCESS);
102 }
103 assert(opts.num_dsps != 0 && opts.num_eves != 0);
104 if (opts.num_frames == 0)
105 opts.num_frames = (opts.is_camera_input || opts.is_video_input) ?
106 NUM_VIDEO_FRAMES :
107 (opts.input_file.empty() ? DEFAULT_INPUT_FRAMES : 1);
108 if (opts.input_file.empty())
109 cout << "Input: " << DEFAULT_INPUT << endl;
110 else
111 cout << "Input: " << opts.input_file << endl;
113 // Get object class table
114 if ((object_class_table = GetObjectClassTable(opts.config)) == nullptr)
115 {
116 cout << "No object classes defined for this config." << endl;
117 return EXIT_FAILURE;
118 }
120 // Run network
121 bool status = RunConfiguration(opts);
122 if (!status)
123 {
124 cout << "ssd_multibox FAILED" << endl;
125 return EXIT_FAILURE;
126 }
128 cout << "ssd_multibox PASSED" << endl;
129 return EXIT_SUCCESS;
130 }
132 bool RunConfiguration(const cmdline_opts_t& opts)
133 {
134 // Read the TI DL configuration file
135 Configuration c;
136 std::string config_file = "../test/testvecs/config/infer/tidl_config_"
137 + opts.config + ".txt";
138 bool status = c.ReadFromFile(config_file);
139 if (!status)
140 {
141 cerr << "Error in configuration file: " << config_file << endl;
142 return false;
143 }
144 c.enableApiTrace = opts.verbose;
146 // setup camera/video input
147 VideoCapture cap;
148 if (! SetVideoInputOutput(cap, opts, "SSD_Multibox")) return false;
150 try
151 {
152 // Create Executors with the approriate core type, number of cores
153 // and configuration specified
154 // EVE will run layersGroupId 1 in the network, while
155 // DSP will run layersGroupId 2 in the network
156 Executor* e_eve = CreateExecutor(DeviceType::EVE, opts.num_eves, c, 1);
157 Executor* e_dsp = CreateExecutor(DeviceType::DSP, opts.num_dsps, c, 2);
159 // Construct ExecutionObjectPipeline that utilizes multiple
160 // ExecutionObjects to process a single frame, each ExecutionObject
161 // processes one layerGroup of the network
162 vector<ExecutionObjectPipeline *> eops;
163 for (uint32_t i = 0; i < max(opts.num_eves, opts.num_dsps); i++)
164 eops.push_back(new ExecutionObjectPipeline(
165 {(*e_eve)[i%opts.num_eves], (*e_dsp)[i%opts.num_dsps]}));
166 uint32_t num_eops = eops.size();
168 // Allocate input/output memory for each EOP
169 AllocateMemory(eops);
171 chrono::time_point<chrono::steady_clock> tloop0, tloop1;
172 tloop0 = chrono::steady_clock::now();
174 // Process frames with available eops in a pipelined manner
175 // additional num_eops iterations to flush pipeline (epilogue)
176 for (uint32_t frame_idx = 0;
177 frame_idx < opts.num_frames + num_eops; frame_idx++)
178 {
179 ExecutionObjectPipeline* eop = eops[frame_idx % num_eops];
181 // Wait for previous frame on the same eop to finish processing
182 if (eop->ProcessFrameWait())
183 {
184 ReportTime(eop);
185 WriteFrameOutput(*eop, c, opts);
186 }
188 // Read a frame and start processing it with current eo
189 if (ReadFrame(*eop, frame_idx, c, opts, cap))
190 eop->ProcessFrameStartAsync();
191 }
193 tloop1 = chrono::steady_clock::now();
194 chrono::duration<float> elapsed = tloop1 - tloop0;
195 cout << "Loop total time (including read/write/opencv/print/etc): "
196 << setw(6) << setprecision(4)
197 << (elapsed.count() * 1000) << "ms" << endl;
199 FreeMemory(eops);
200 for (auto eop : eops) delete eop;
201 delete e_eve;
202 delete e_dsp;
203 }
204 catch (tidl::Exception &e)
205 {
206 cerr << e.what() << endl;
207 status = false;
208 }
210 return status;
211 }
213 // Create an Executor with the specified type and number of EOs
214 Executor* CreateExecutor(DeviceType dt, int num, const Configuration& c,
215 int layers_group_id)
216 {
217 if (num == 0) return nullptr;
219 DeviceIds ids;
220 for (uint32_t i = 0; i < num; i++)
221 ids.insert(static_cast<DeviceId>(i));
223 return new Executor(dt, ids, c, layers_group_id);
224 }
226 bool ReadFrame(ExecutionObjectPipeline& eop, int frame_idx,
227 const Configuration& c, const cmdline_opts_t& opts,
228 VideoCapture &cap)
229 {
230 if (frame_idx >= opts.num_frames)
231 return false;
232 eop.SetFrameIndex(frame_idx);
234 char* frame_buffer = eop.GetInputBufferPtr();
235 assert (frame_buffer != nullptr);
236 int channel_size = c.inWidth * c.inHeight;
238 Mat image;
239 if (!opts.is_camera_input && !opts.is_video_input)
240 {
241 if (opts.input_file.empty())
242 {
243 ifstream ifs(DEFAULT_INPUT, ios::binary);
244 ifs.seekg((frame_idx % DEFAULT_INPUT_FRAMES) * channel_size * 3);
245 ifs.read(frame_buffer, channel_size * 3);
246 bool ifs_status = ifs.good();
247 ifs.close();
248 orig_width = c.inWidth;
249 orig_height = c.inHeight;
250 return ifs_status; // already PreProc-ed
251 }
252 else
253 {
254 image = cv::imread(opts.input_file, CV_LOAD_IMAGE_COLOR);
255 if (image.empty())
256 {
257 cerr << "Unable to read from: " << opts.input_file << endl;
258 return false;
259 }
260 }
261 }
262 else
263 {
264 // 640x480 camera input, process one in every 5 frames,
265 // can adjust number of skipped frames to match real time processing
266 if (! cap.grab()) return false;
267 if (! cap.grab()) return false;
268 if (! cap.grab()) return false;
269 if (! cap.grab()) return false;
270 if (! cap.grab()) return false;
271 if (! cap.retrieve(image)) return false;
272 }
274 // scale to network input size
275 Mat s_image, bgr_frames[3];
276 orig_width = image.cols;
277 orig_height = image.rows;
278 cv::resize(image, s_image, Size(c.inWidth, c.inHeight),
279 0, 0, cv::INTER_AREA);
280 cv::split(s_image, bgr_frames);
281 memcpy(frame_buffer, bgr_frames[0].ptr(), channel_size);
282 memcpy(frame_buffer+1*channel_size, bgr_frames[1].ptr(), channel_size);
283 memcpy(frame_buffer+2*channel_size, bgr_frames[2].ptr(), channel_size);
284 return true;
285 }
287 // Create frame with boxes drawn around classified objects
288 bool WriteFrameOutput(const ExecutionObjectPipeline& eop,
289 const Configuration& c, const cmdline_opts_t& opts)
290 {
291 // Asseembly original frame
292 int width = c.inWidth;
293 int height = c.inHeight;
294 int channel_size = width * height;
295 Mat frame, r_frame, bgr[3];
297 unsigned char *in = (unsigned char *) eop.GetInputBufferPtr();
298 bgr[0] = Mat(height, width, CV_8UC(1), in);
299 bgr[1] = Mat(height, width, CV_8UC(1), in + channel_size);
300 bgr[2] = Mat(height, width, CV_8UC(1), in + channel_size*2);
301 cv::merge(bgr, 3, frame);
303 int frame_index = eop.GetFrameIndex();
304 char outfile_name[64];
305 if (opts.input_file.empty())
306 {
307 snprintf(outfile_name, 64, "frame_%d.png", frame_index);
308 cv::imwrite(outfile_name, frame);
309 printf("Saving frame %d to: %s\n", frame_index, outfile_name);
310 }
312 // Draw boxes around classified objects
313 float *out = (float *) eop.GetOutputBufferPtr();
314 int num_floats = eop.GetOutputBufferSizeInBytes() / sizeof(float);
315 for (int i = 0; i < num_floats / 7; i++)
316 {
317 int index = (int) out[i * 7 + 0];
318 if (index < 0) break;
320 int label = (int) out[i * 7 + 1];
321 int xmin = (int) (out[i * 7 + 3] * width);
322 int ymin = (int) (out[i * 7 + 4] * height);
323 int xmax = (int) (out[i * 7 + 5] * width);
324 int ymax = (int) (out[i * 7 + 6] * height);
326 object_class_t *object_class = GetObjectClass(object_class_table,
327 label);
328 if (object_class == nullptr) continue;
330 #if 0
331 printf("(%d, %d) -> (%d, %d): %s, score=%f\n",
332 xmin, ymin, xmax, ymax, object_class->label, score);
333 #endif
335 cv::rectangle(frame, Point(xmin, ymin), Point(xmax, ymax),
336 Scalar(object_class->color.blue,
337 object_class->color.green,
338 object_class->color.red), 2);
339 }
341 // Resize to output width/height, keep aspect ratio
342 uint32_t output_width = opts.output_width;
343 if (output_width == 0) output_width = orig_width;
344 uint32_t output_height = (output_width*1.0f) / orig_width * orig_height;
345 cv::resize(frame, r_frame, Size(output_width, output_height));
347 if (opts.is_camera_input || opts.is_video_input)
348 {
349 cv::imshow("SSD_Multibox", r_frame);
350 waitKey(1);
351 }
352 else
353 {
354 snprintf(outfile_name, 64, "multibox_%d.png", frame_index);
355 cv::imwrite(outfile_name, r_frame);
356 printf("Saving frame %d with SSD multiboxes to: %s\n",
357 frame_index, outfile_name);
358 }
360 return true;
361 }
363 void DisplayHelp()
364 {
365 std::cout <<
366 "Usage: ssd_multibox\n"
367 " Will run partitioned ssd_multibox network to perform "
368 "multi-objects detection\n"
369 " and classification. First part of network "
370 "(layersGroupId 1) runs on EVE,\n"
371 " second part (layersGroupId 2) runs on DSP.\n"
372 " Use -c to run a different segmentation network. Default is jdetnet.\n"
373 "Optional arguments:\n"
374 " -c <config> Valid configs: jdetnet \n"
375 " -d <number> Number of dsp cores to use\n"
376 " -e <number> Number of eve cores to use\n"
377 " -i <image> Path to the image file as input\n"
378 " Default are 9 frames in testvecs\n"
379 " -i camera<number> Use camera as input\n"
380 " video input port: /dev/video<number>\n"
381 " -i <name>.{mp4,mov,avi} Use video file as input\n"
382 " -f <number> Number of frames to process\n"
383 " -w <number> Output image/video width\n"
384 " -v Verbose output during execution\n"
385 " -h Help\n";
386 }