Dataset: add READMEs, organize scripts, update .gitignore
- Add README.md to all 16 dataset directories with script references - Centralize generation scripts under scripts/ with full README - Update .gitignore to cover all data directories, keep only metadata - Remove redundant CCPD/.gitignore (parent covers same rules) - Remove stale scripts/test/ (254MB pipeline residue) - Fix label parser reference: scripts are authoritative source of truth
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@@ -39,4 +39,4 @@ Write-Host "可执行文件: $buildDir\Release\plate_swap.exe"
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# 使用示例
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Write-Host ""
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Write-Host "用法示例:"
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Write-Host " .\build\Release\plate_swap.exe --ccpd-dir ./CCPD/CCPD2019/ccpd_base --plate-type police --plate-pool ./output/plate_pool --num 500 --workers 32 --fast"
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Write-Host " .\build\Release\plate_swap.exe --ccpd-dir ./CCPD/CCPD2019/ccpd_base --plate-type police --plate-pool ./output/plate_pool --num 500 --workers 32"
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@@ -49,6 +49,8 @@ from plate_number import (
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# 类型配置
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PLATE_TYPES = [
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('blue', 'blue', generate_plate_number_blue),
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('green', 'green_car', lambda: generate_plate_number_blue(length=8)),
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('police', 'white', generate_plate_number_white),
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('army', 'white_army', generate_plate_number_army),
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('gangao', 'black', generate_plate_number_black_gangao),
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@@ -18,7 +18,6 @@ struct Config {
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string plate_pool_dir;
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int num_images = 500;
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unsigned workers = thread::hardware_concurrency();
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bool fast = false;
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int seed = 42;
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int h_shift = 0, s_scale = 100, v_scale = 100;
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};
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@@ -50,7 +49,6 @@ Config parse_args(int argc, char* argv[]) {
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else if (arg == "--num" && i+1 < argc) cfg.num_images = stoi(argv[++i]);
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else if (arg == "--workers" && i+1 < argc) cfg.workers = stoi(argv[++i]);
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else if (arg == "--seed" && i+1 < argc) cfg.seed = stoi(argv[++i]);
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else if (arg == "--fast") cfg.fast = true;
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else if (arg == "--h-shift" && i+1 < argc) cfg.h_shift = stoi(argv[++i]);
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else if (arg == "--s-scale" && i+1 < argc) cfg.s_scale = stoi(argv[++i]);
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else if (arg == "--v-scale" && i+1 < argc) cfg.v_scale = stoi(argv[++i]);
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@@ -103,7 +101,6 @@ int main(int argc, char* argv[]) {
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cerr << " --plate-pool <dir> Plate pool directory (required)" << endl;
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cerr << " --num <N> Number of images (default 500)" << endl;
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cerr << " --workers <N> Thread count (default all cores)" << endl;
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cerr << " --fast Fast mode (skip degradation)" << endl;
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return 1;
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}
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@@ -111,7 +108,6 @@ int main(int argc, char* argv[]) {
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cout << "Type: " << cfg.plate_type << endl;
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cout << "Threads: " << cfg.workers << endl;
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cout << "Target: " << cfg.num_images << " images" << endl;
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cout << "Fast: " << (cfg.fast ? "yes" : "no") << endl;
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if (cfg.plate_pool_dir.empty()) {
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cerr << "[ERROR] --plate-pool is required" << endl;
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@@ -153,7 +149,6 @@ int main(int argc, char* argv[]) {
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SwapConfig swap_cfg;
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swap_cfg.plate_type = cfg.plate_type;
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swap_cfg.output_dir = cfg.output_dir;
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swap_cfg.fast_mode = cfg.fast;
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swap_cfg.h_shift = cfg.h_shift;
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swap_cfg.s_scale = cfg.s_scale;
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swap_cfg.v_scale = cfg.v_scale;
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@@ -184,6 +184,8 @@ static string bg_color_of(const string& plate_type) {
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if (plate_type == "lingguan_old" || plate_type == "lingguan_new") return "black";
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if (plate_type == "coach") return "yellow";
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if (plate_type == "new_energy") return "green_truck";
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if (plate_type == "blue") return "blue";
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if (plate_type == "green") return "green_car";
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return "white";
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}
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@@ -322,7 +324,7 @@ Mat match_plate_color(const Mat& synthetic, const Mat& orig_roi,
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// 白/绿牌
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Scalar color_cast(white_ref[0]/ref_mean, white_ref[1]/ref_mean, white_ref[2]/ref_mean);
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float strength = (bg_color == "green_truck") ? 1.5f : 1.0f;
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float strength = (bg_color == "green_truck" || bg_color == "green_car") ? 1.5f : 1.0f;
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Scalar amplified(1.0f + (color_cast[0]-1.0f)*strength, 1.0f+(color_cast[1]-1.0f)*strength, 1.0f+(color_cast[2]-1.0f)*strength);
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amplified[0] = std::clamp((float)amplified[0], 0.85f, 1.15f);
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amplified[1] = std::clamp((float)amplified[1], 0.85f, 1.15f);
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@@ -359,7 +361,8 @@ Mat fix_bg_color(const Mat& plate, const string& bg_color,
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int h_lo = 0, h_hi = 180;
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if (bg_color == "yellow") { h_lo = 15; h_hi = 50; }
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else if (bg_color == "green_truck") { h_lo = 40; h_hi = 85; }
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else if (bg_color == "green_truck" || bg_color == "green_car") { h_lo = 40; h_hi = 85; }
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else if (bg_color == "blue") { h_lo = 90; h_hi = 130; }
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Mat hsv;
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cvtColor(plate, hsv, COLOR_BGR2HSV);
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@@ -629,7 +632,7 @@ bool process_single(const string& img_path, const SwapConfig& cfg,
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if (current_w > 10 && abs(target_w - current_w) > 10) {
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float l_ratio = target_w / current_w;
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float min_c = 0.5f, max_c = 1.1f;
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if (bg_color == "green_truck" || bg_color == "yellow") { min_c = 0.4f; max_c = 1.0f; }
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if (bg_color == "green_truck" || bg_color == "green_car" || bg_color == "yellow") { min_c = 0.4f; max_c = 1.0f; }
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else if (bg_color == "black" || bg_color == "black_shi") { min_c = 0.3f; max_c = 1.2f; }
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l_ratio = std::clamp(l_ratio, min_c, max_c);
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@@ -650,38 +653,16 @@ bool process_single(const string& img_path, const SwapConfig& cfg,
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}
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// 8. Degradation
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if (!cfg.fast_mode)
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matched = degrade_plate(matched);
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matched = degrade_plate(matched);
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// 9-11. Warp + blend + noise
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auto [warped, mask] = warp_plate_back(matched, meta.corners, Size(w_img, h_img));
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Mat blended = feather_blend(img_orig, warped, mask);
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Mat final = match_noise(blended, img_orig, mask);
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// 12. Save with pinyin tags
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// 12. Save with original Chinese plate number (imwrite_unicode supports UTF-8)
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string stem = fp.stem().string();
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// Convert Chinese plate markers to ASCII tags
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string tag = plate_number;
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// Manual pinyin mapping for common plate characters (UTF-8 byte sequences)
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// 港=E6B8AF 澳=E6BEB3 警=E8ADA6 使=E4BDBF 领=E9A286 学=E5ADA6
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struct { const char* utf8; const char* py; } map[] = {
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{"\xE6\xB8\xAF", "GANG"}, {"\xE6\xBE\xB3", "AO"},
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{"\xE8\xAD\xA6", "JING"}, {"\xE4\xBD\xBF", "SHI"},
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{"\xE9\xA2\x86", "LING"}, {"\xE5\xAD\xA6", "XUE"},
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};
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for (auto& m : map) {
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size_t pos = 0;
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while ((pos = tag.find(m.utf8, pos)) != string::npos) {
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tag.replace(pos, 3, m.py);
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pos += strlen(m.py);
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}
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}
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// Remove any remaining non-ASCII
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string clean;
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for (char c : tag) {
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if ((unsigned char)c < 128) clean += c;
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}
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string out_name = stem + "__" + cfg.plate_type + "__" + clean + ".jpg";
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string out_name = stem + "__" + cfg.plate_type + "__" + plate_number + ".jpg";
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string ccpd_subdir = fp.parent_path().filename().string();
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fs::path out_dir = fs::path(cfg.output_dir) / ccpd_subdir / cfg.plate_type;
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fs::create_directories(out_dir);
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@@ -34,7 +34,6 @@ struct SwapConfig {
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std::string plate_type;
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std::string output_dir;
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int h_shift = 0, s_scale = 100, v_scale = 100;
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bool fast_mode = false;
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};
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// 单张处理 (pre-parsed meta 避免重复解析)
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@@ -45,8 +45,10 @@ from plate_number import (
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# ── 车牌类型 ──
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PLATE_TYPES = [
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('blue', '蓝牌', generate_plate_number_blue),
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('green_car', '小新能源', lambda: generate_plate_number_blue(length=8)),
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('yellow', '教练车', generate_plate_number_yellow_xue),
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('green_truck','新能源', lambda: generate_plate_number_blue(length=8)),
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('green_truck','大新能源', lambda: generate_plate_number_blue(length=8)),
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('white', '警车', generate_plate_number_white),
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('white_army', '军车', generate_plate_number_army),
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('black', '港澳', generate_plate_number_black_gangao),
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@@ -113,7 +115,8 @@ def adjust_plate(plate_bgr, bg_color, h_shift, s_scale, v_scale):
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return plate_bgr.copy()
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hue_ranges = {
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'yellow': (15, 50), 'green_truck': (40, 85),
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'yellow': (15, 50), 'green_truck': (40, 85), 'green_car': (40, 85),
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'blue': (90, 130),
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'white': (0, 180), 'white_army': (0, 180),
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'black': (0, 180), 'black_shi': (0, 180),
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}
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@@ -182,7 +185,7 @@ def update_display(*_args):
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(w + 10, 25), cv2.FONT_HERSHEY_SIMPLEX, 0.55, (0, 255, 200), 1)
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# 类型标签
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cv2.putText(display, f"[{current_type_idx+1}/9] {label}",
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cv2.putText(display, f"[{current_type_idx+1}/{len(PLATE_TYPES)}] {label}",
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(10, display.shape[0] - 10),
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cv2.FONT_HERSHEY_SIMPLEX, 0.5, (180, 180, 180), 1)
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@@ -206,7 +209,8 @@ def save_params():
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'# Format: (h_shift, s_scale_percent, v_scale_percent)',
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'',
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'PLATE_COLOR_PROFILE = {']
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for bg_color in ['yellow', 'green_truck', 'white', 'white_army', 'black', 'black_shi']:
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for bg_color in ['yellow', 'green_truck', 'green_car', 'blue',
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'white', 'white_army', 'black', 'black_shi']:
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p = params.get(bg_color, {'h_shift': 0, 's_scale': 100, 'v_scale': 100})
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lines.append(f" '{bg_color}': ({p['h_shift']}, {p['s_scale']}, {p['v_scale']}),")
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lines.append('}')
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@@ -219,19 +223,26 @@ def save_params():
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def on_key(key):
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global current_type_idx, synthetic_plate
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# keys: 1-9, 0(=10), -(=11) — 切换车牌类型
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idx = -1
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if ord('1') <= key <= ord('9'):
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idx = key - ord('1')
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if idx < len(PLATE_TYPES):
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current_type_idx = idx
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# 切换类型时复位 trackbar 到该类型已保存的参数
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bg_color = PLATE_TYPES[current_type_idx][0]
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p = load_params(bg_color)
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cv2.setTrackbarPos('H offset', 'Color Tuner', p['h_shift'] + 30)
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cv2.setTrackbarPos('S scale', 'Color Tuner', p['s_scale'])
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cv2.setTrackbarPos('V scale', 'Color Tuner', p['v_scale'])
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# 生成新车牌
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synthetic_plate, _, _ = generate_plate(current_type_idx)
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update_display()
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elif key == ord('0'):
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idx = 9
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elif key == ord('-'):
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idx = 10
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if 0 <= idx < len(PLATE_TYPES):
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current_type_idx = idx
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# 切换类型时复位 trackbar 到该类型已保存的参数
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bg_color = PLATE_TYPES[current_type_idx][0]
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p = load_params(bg_color)
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cv2.setTrackbarPos('H offset', 'Color Tuner', p['h_shift'] + 30)
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cv2.setTrackbarPos('S scale', 'Color Tuner', p['s_scale'])
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cv2.setTrackbarPos('V scale', 'Color Tuner', p['v_scale'])
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# 生成新车牌
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synthetic_plate, _, _ = generate_plate(current_type_idx)
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update_display()
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elif key == ord('r') or key == ord('R'):
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bg_color = PLATE_TYPES[current_type_idx][0]
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params[bg_color] = {'h_shift': 0, 's_scale': 100, 'v_scale': 100}
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@@ -3,8 +3,10 @@
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# Format: (h_shift, s_scale_percent, v_scale_percent)
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PLATE_COLOR_PROFILE = {
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'yellow': (-2, 150, 100),
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'green_truck': (0, 100, 100),
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'yellow': (0, 150, 150),
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'green_truck': (0, 100, 150),
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'green_car': (-4, 69, 92),
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'blue': (-7, 150, 150),
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'white': (0, 100, 100),
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'white_army': (0, 100, 100),
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'black': (0, 100, 100),
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@@ -156,6 +156,16 @@ PLATE_TYPE_CONFIG = {
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'generator': lambda: generate_plate_number_blue(length=8),
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'description': '大型新能源'
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},
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'blue': {
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'bg_color': 'blue',
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'generator': generate_plate_number_blue,
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'description': '蓝牌小型汽车'
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},
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'green': {
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'bg_color': 'green_car',
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'generator': lambda: generate_plate_number_blue(length=8),
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'description': '小型新能源'
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},
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}
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@@ -407,7 +417,7 @@ def match_plate_color(synthetic_plate: np.ndarray,
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color_cast = white_ref / ref_mean
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strength_map = {
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'white': 1.0, 'white_army': 1.0,
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'green_truck': 1.5,
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'blue': 1.0, 'green_car': 1.5, 'green_truck': 1.5,
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}
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strength = strength_map.get(bg_color, 2.0)
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@@ -492,7 +502,8 @@ def fix_plate_bg_color(plate_bgr: np.ndarray, bg_color: str) -> np.ndarray:
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# 色相范围
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hue_ranges = {
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'yellow': (15, 50), 'green_truck': (40, 85),
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'yellow': (15, 50), 'green_truck': (40, 85), 'green_car': (40, 85),
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'blue': (90, 130),
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'white': (0, 180), 'white_army': (0, 180),
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'black': (0, 180), 'black_shi': (0, 180),
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}
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@@ -741,11 +752,10 @@ def match_image_quality(result: np.ndarray,
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_worker_pipeline = None
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def _worker_init(plate_type, fast):
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def _worker_init(plate_type):
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"""进程初始化：每个 worker 启动时调用一次（加载字体、底板缓存）"""
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global _worker_pipeline
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_worker_pipeline = PlateSwapPipeline(plate_type=plate_type)
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_worker_pipeline._fast_mode = fast
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def _worker_process_single(args):
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@@ -791,9 +801,6 @@ class PlateSwapPipeline:
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font_dir = str(_GENERATOR_DIR / 'font_model')
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self.generator = MultiPlateGenerator(plate_model_dir, font_dir)
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# 快速模式标志（多进程时由 _worker_process_single 设置）
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self._fast_mode = False
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def generate_plate_number(self) -> str:
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"""生成随机特殊车牌号码"""
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return self.number_generator()
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@@ -864,7 +871,8 @@ class PlateSwapPipeline:
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# 不同底板色用不同下限，防止白底变灰、绿牌变亮
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clip_cfg = {
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'white': (0.5, 1.1), 'white_army': (0.5, 1.1),
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'green_truck': (0.4, 1.0),
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'blue': (0.5, 1.1),
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'green_truck': (0.4, 1.0), 'green_car': (0.4, 1.0),
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'yellow': (0.4, 1.0),
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'black': (0.3, 1.2), 'black_shi': (0.3, 1.2),
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}
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@@ -879,16 +887,15 @@ class PlateSwapPipeline:
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matched_plate = (matched_plate.astype(np.float32) * effective_ratio)
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matched_plate = np.clip(matched_plate, 0, 255).astype(np.uint8)
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# ---- 8. 退化模拟（快速模式下跳过） ----
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if not self._fast_mode:
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# JPEG 极限压缩
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matched_plate = jpeg_compress(matched_plate, quality=2)
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# 降采样→升采样 模拟马赛克/像素化
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h_p, w_p = matched_plate.shape[:2]
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small = cv2.resize(matched_plate, (w_p // 4, h_p // 4), interpolation=cv2.INTER_LINEAR)
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matched_plate = cv2.resize(small, (w_p, h_p), interpolation=cv2.INTER_NEAREST)
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# 较强模糊
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matched_plate = cv2.GaussianBlur(matched_plate, (5, 5), 1.5)
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# ---- 8. 退化模拟 ----
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# JPEG 极限压缩
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matched_plate = jpeg_compress(matched_plate, quality=2)
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# 降采样→升采样 模拟马赛克/像素化
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h_p, w_p = matched_plate.shape[:2]
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small = cv2.resize(matched_plate, (w_p // 4, h_p // 4), interpolation=cv2.INTER_LINEAR)
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matched_plate = cv2.resize(small, (w_p, h_p), interpolation=cv2.INTER_NEAREST)
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# 较强模糊
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matched_plate = cv2.GaussianBlur(matched_plate, (5, 5), 1.5)
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# ---- 9. 透视变换回贴 ----
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warped, plate_mask = warp_plate_back(
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@@ -903,7 +910,7 @@ class PlateSwapPipeline:
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# ---- 12. 保存 ----
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basename = Path(filename).stem
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out_name = f"{basename}_{self.plate_type}_{new_plate_number}.jpg"
|
||||
out_name = f"{basename}__{self.plate_type}__{new_plate_number}.jpg"
|
||||
out_path = os.path.join(output_dir, out_name)
|
||||
_imwrite_unicode(out_path, final, [cv2.IMWRITE_JPEG_QUALITY, 95])
|
||||
|
||||
@@ -927,8 +934,7 @@ class PlateSwapPipeline:
|
||||
num_images: int = 500,
|
||||
preview: bool = False,
|
||||
seed: int = 42,
|
||||
workers: int = 1,
|
||||
fast: bool = False):
|
||||
workers: int = 1):
|
||||
"""
|
||||
批量处理 CCPD 图片目录。
|
||||
|
||||
@@ -939,7 +945,6 @@ class PlateSwapPipeline:
|
||||
preview: 是否保存调试中间结果
|
||||
seed: 随机种子
|
||||
workers: 并行进程数 (1=单进程, >1=多进程)
|
||||
fast: 快速模式 (跳过退化模拟步骤)
|
||||
"""
|
||||
random.seed(seed)
|
||||
np.random.seed(seed)
|
||||
@@ -969,8 +974,6 @@ class PlateSwapPipeline:
|
||||
print(f"目标生成数: {num_images}")
|
||||
print(f"输出目录: {output_dir}")
|
||||
print(f"并行进程: {workers}" + (" (多核加速)" if workers > 1 else ""))
|
||||
if fast:
|
||||
print(f"快速模式: 跳过退化模拟")
|
||||
print("-" * 60)
|
||||
|
||||
import time
|
||||
@@ -984,7 +987,7 @@ class PlateSwapPipeline:
|
||||
else:
|
||||
# 多进程模式
|
||||
success, failed = self._process_parallel(
|
||||
image_paths, output_dir, num_images, preview, workers, fast
|
||||
image_paths, output_dir, num_images, preview, workers
|
||||
)
|
||||
|
||||
elapsed = time.perf_counter() - t0
|
||||
@@ -1013,7 +1016,7 @@ class PlateSwapPipeline:
|
||||
return success, failed
|
||||
|
||||
def _process_parallel(self, image_paths, output_dir, num_images,
|
||||
preview, workers, fast):
|
||||
preview, workers):
|
||||
"""多进程并行处理（worker 复用 Pipeline，仅初始化一次）"""
|
||||
from multiprocessing import Pool, cpu_count
|
||||
n_procs = min(workers, cpu_count())
|
||||
@@ -1022,7 +1025,7 @@ class PlateSwapPipeline:
|
||||
|
||||
# 每个 worker 启动时加载一次 Pipeline（含字体、底板缓存）
|
||||
with Pool(n_procs, initializer=_worker_init,
|
||||
initargs=(self.plate_type, fast)) as pool:
|
||||
initargs=(self.plate_type,)) as pool:
|
||||
# 参数精简: (img_path, output_dir, preview_bool)
|
||||
args = [
|
||||
(p, output_dir, (preview and i < 10))
|
||||
@@ -1074,9 +1077,6 @@ def main():
|
||||
help='随机种子 (默认: 42)')
|
||||
parser.add_argument('--workers', type=int, default=1,
|
||||
help='并行进程数 (默认: 1, 建议设为CPU核心数)')
|
||||
parser.add_argument('--fast', action='store_true',
|
||||
help='快速模式：跳过退化模拟，速度提升约40%%')
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
ccpd_dirs = [d.strip() for d in args.ccpd_dir.split(',') if d.strip()]
|
||||
@@ -1088,7 +1088,6 @@ def main():
|
||||
preview=args.preview,
|
||||
seed=args.seed,
|
||||
workers=args.workers,
|
||||
fast=args.fast,
|
||||
)
|
||||
|
||||
|
||||
|
||||
Reference in new issue
Block a user