mirror of
https://github.com/yynps737/dnf-auto-cloud.git
synced 2026-05-07 05:25:42 +08:00
Initial commit: DNF automated script with YOLO8m
This commit is contained in:
root
17
.gitignore
vendored
17
.gitignore
vendored
@@ -1,5 +1,4 @@
|
||||
# 创建.gitignore文件排除不需要的文件
|
||||
cat > .gitignore << EOF
|
||||
# Python缓存文件
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
*$py.class
|
||||
@@ -7,17 +6,23 @@ __pycache__/
|
||||
.env
|
||||
venv/
|
||||
ENV/
|
||||
|
||||
# 编辑器配置
|
||||
.vscode/
|
||||
.idea/
|
||||
|
||||
# 日志和模型文件
|
||||
*.log
|
||||
*.pt
|
||||
*.pth
|
||||
logs/
|
||||
|
||||
# 训练数据（避免上传大量图像）
|
||||
data/training/images/*
|
||||
data/training/labels/*
|
||||
!data/training/images/.gitkeep
|
||||
!data/training/labels/.gitkeep
|
||||
EOF
|
||||
|
||||
# 确保创建空目录占位符
|
||||
mkdir -p data/training/images data/training/labels
|
||||
touch data/training/images/.gitkeep data/training/labels/.gitkeep
|
||||
# 系统文件
|
||||
.DS_Store
|
||||
Thumbs.db
|
||||
1
config/encryption.key
Normal file
1
config/encryption.key
Normal file
@@ -0,0 +1 @@
|
||||
W5q7WV5ITm9C3UfY1w8FMHgHk6Mv5PysDo0D2r2hXSE=
|
||||
@@ -1,7 +1,7 @@
|
||||
path: data/training
|
||||
train: data/training/images/train
|
||||
val: data/training/images/val
|
||||
test: data/training/images/test
|
||||
path: /workspace/dnf-auto-cloud/data/training
|
||||
train: /workspace/dnf-auto-cloud/data/training/images/train
|
||||
val: /workspace/dnf-auto-cloud/data/training/images/val
|
||||
test: /workspace/dnf-auto-cloud/data/training/images/test
|
||||
nc: 10
|
||||
names:
|
||||
- monster
|
||||
|
||||
BIN
models/weights/F1_curve.png
Normal file
BIN
models/weights/F1_curve.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 166 KiB |
BIN
models/weights/PR_curve.png
Normal file
BIN
models/weights/PR_curve.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 99 KiB |
BIN
models/weights/P_curve.png
Normal file
BIN
models/weights/P_curve.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 146 KiB |
BIN
models/weights/R_curve.png
Normal file
BIN
models/weights/R_curve.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 118 KiB |
BIN
models/weights/confusion_matrix.png
Normal file
BIN
models/weights/confusion_matrix.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 150 KiB |
BIN
models/weights/labels.jpg
Normal file
BIN
models/weights/labels.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 155 KiB |
BIN
models/weights/labels_correlogram.jpg
Normal file
BIN
models/weights/labels_correlogram.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 244 KiB |
101
models/weights/results.csv
Normal file
101
models/weights/results.csv
Normal file
@@ -0,0 +1,101 @@
|
||||
epoch, train/box_loss, train/obj_loss, train/cls_loss, metrics/precision, metrics/recall, metrics/mAP_0.5,metrics/mAP_0.5:0.95, val/box_loss, val/obj_loss, val/cls_loss, x/lr0, x/lr1, x/lr2
|
||||
0, 0.11062, 0.044713, 0.062774, 0.012864, 0.25694, 0.044005, 0.011607, 0.09363, 0.041389, 0.055328, 0.0883, 0.0013, 0.0013
|
||||
1, 0.084386, 0.052809, 0.045843, 0.012305, 0.58135, 0.037866, 0.01087, 0.081148, 0.041847, 0.040951, 0.075673, 0.0026733, 0.0026733
|
||||
2, 0.080052, 0.046154, 0.039956, 0.55511, 0.13355, 0.073915, 0.019121, 0.075842, 0.027031, 0.031986, 0.063019, 0.0040188, 0.0040188
|
||||
3, 0.078225, 0.032642, 0.03222, 0.89008, 0.1593, 0.2019, 0.093216, 0.081309, 0.020676, 0.028984, 0.050337, 0.0053367, 0.0053367
|
||||
4, 0.075672, 0.030229, 0.030481, 0.38578, 0.42212, 0.20752, 0.055837, 0.088352, 0.018589, 0.026398, 0.037627, 0.0066268, 0.0066268
|
||||
5, 0.081446, 0.027271, 0.0294, 0.73021, 0.30357, 0.3954, 0.14948, 0.085555, 0.016193, 0.023893, 0.024889, 0.0078891, 0.0078891
|
||||
6, 0.075361, 0.023581, 0.027368, 0.45782, 0.62595, 0.29554, 0.1066, 0.090591, 0.017099, 0.022596, 0.012124, 0.0091238, 0.0091238
|
||||
7, 0.076797, 0.022953, 0.026967, 0.46326, 0.63058, 0.37613, 0.10864, 0.080876, 0.019985, 0.021849, 0.009307, 0.009307, 0.009307
|
||||
8, 0.069277, 0.021624, 0.025897, 0.44857, 0.52412, 0.39575, 0.1484, 0.08447, 0.027252, 0.023365, 0.009307, 0.009307, 0.009307
|
||||
9, 0.069657, 0.021723, 0.025119, 0.68102, 0.69233, 0.66763, 0.25607, 0.061653, 0.018906, 0.018222, 0.009208, 0.009208, 0.009208
|
||||
10, 0.057849, 0.020393, 0.025134, 0.58782, 0.6286, 0.62221, 0.38337, 0.053783, 0.017891, 0.017056, 0.009109, 0.009109, 0.009109
|
||||
11, 0.055896, 0.018569, 0.020781, 0.65791, 0.70455, 0.84397, 0.38415, 0.054539, 0.015846, 0.015294, 0.00901, 0.00901, 0.00901
|
||||
12, 0.055146, 0.019553, 0.020457, 0.61275, 0.61576, 0.69215, 0.35269, 0.054875, 0.01627, 0.015222, 0.008911, 0.008911, 0.008911
|
||||
13, 0.051287, 0.01728, 0.019606, 0.61733, 0.67584, 0.77896, 0.44407, 0.054481, 0.015491, 0.012888, 0.008812, 0.008812, 0.008812
|
||||
14, 0.049833, 0.017423, 0.017959, 0.77359, 0.65157, 0.79625, 0.32758, 0.050235, 0.015112, 0.011866, 0.008713, 0.008713, 0.008713
|
||||
15, 0.046434, 0.015612, 0.018171, 0.7663, 0.66557, 0.86331, 0.38905, 0.043334, 0.013628, 0.013504, 0.008614, 0.008614, 0.008614
|
||||
16, 0.046136, 0.016711, 0.01776, 0.83936, 0.64404, 0.90648, 0.43725, 0.043066, 0.013478, 0.012336, 0.008515, 0.008515, 0.008515
|
||||
17, 0.043906, 0.017081, 0.017746, 0.8748, 0.65369, 0.85847, 0.42247, 0.042315, 0.013261, 0.010645, 0.008416, 0.008416, 0.008416
|
||||
18, 0.042014, 0.01525, 0.014397, 0.94607, 0.65739, 0.95437, 0.5543, 0.037817, 0.012558, 0.0096827, 0.008317, 0.008317, 0.008317
|
||||
19, 0.041375, 0.016451, 0.014576, 0.89657, 0.67084, 0.96508, 0.57767, 0.038009, 0.012259, 0.0095654, 0.008218, 0.008218, 0.008218
|
||||
20, 0.041926, 0.016043, 0.013606, 0.66705, 0.71925, 0.84926, 0.53664, 0.035998, 0.011994, 0.0097508, 0.008119, 0.008119, 0.008119
|
||||
21, 0.037189, 0.014944, 0.01277, 0.75159, 0.68896, 0.79352, 0.5062, 0.043335, 0.012637, 0.0087438, 0.00802, 0.00802, 0.00802
|
||||
22, 0.038953, 0.016303, 0.012446, 0.9459, 0.71773, 0.96028, 0.52056, 0.037898, 0.012242, 0.0083613, 0.007921, 0.007921, 0.007921
|
||||
23, 0.036443, 0.015973, 0.011707, 0.88666, 0.70157, 0.96726, 0.66801, 0.035636, 0.012009, 0.0079827, 0.007822, 0.007822, 0.007822
|
||||
24, 0.034551, 0.015153, 0.011661, 0.8874, 0.65796, 0.97283, 0.67398, 0.034467, 0.011672, 0.0087318, 0.007723, 0.007723, 0.007723
|
||||
25, 0.035314, 0.013907, 0.01145, 0.9537, 0.71451, 0.98817, 0.69635, 0.02786, 0.011174, 0.0084147, 0.007624, 0.007624, 0.007624
|
||||
26, 0.034133, 0.013862, 0.011951, 0.72453, 0.89518, 0.98299, 0.60003, 0.034185, 0.011813, 0.0096507, 0.007525, 0.007525, 0.007525
|
||||
27, 0.034647, 0.013215, 0.010499, 0.71244, 0.98283, 0.98149, 0.63632, 0.030054, 0.011369, 0.0081987, 0.007426, 0.007426, 0.007426
|
||||
28, 0.03294, 0.01456, 0.011796, 0.73212, 0.97058, 0.96119, 0.73927, 0.026755, 0.01094, 0.010894, 0.007327, 0.007327, 0.007327
|
||||
29, 0.030987, 0.014169, 0.0097715, 0.67805, 0.97321, 0.96337, 0.67988, 0.02935, 0.011142, 0.0090103, 0.007228, 0.007228, 0.007228
|
||||
30, 0.030368, 0.011704, 0.0094685, 0.72498, 0.98016, 0.98725, 0.68643, 0.027223, 0.010579, 0.0074158, 0.007129, 0.007129, 0.007129
|
||||
31, 0.030643, 0.012915, 0.009158, 0.84399, 0.98909, 0.98542, 0.74619, 0.026265, 0.010507, 0.006691, 0.00703, 0.00703, 0.00703
|
||||
32, 0.029583, 0.012493, 0.0090232, 0.79042, 0.98909, 0.98082, 0.6973, 0.029134, 0.010659, 0.0066166, 0.006931, 0.006931, 0.006931
|
||||
33, 0.02909, 0.014057, 0.0093144, 0.84826, 0.98909, 0.98338, 0.74119, 0.029363, 0.010697, 0.0061455, 0.006832, 0.006832, 0.006832
|
||||
34, 0.030618, 0.013529, 0.0085338, 0.94853, 0.98909, 0.99382, 0.71363, 0.022315, 0.0099039, 0.0059595, 0.006733, 0.006733, 0.006733
|
||||
35, 0.027751, 0.01337, 0.0094638, 0.92628, 0.98902, 0.99414, 0.71161, 0.026125, 0.010315, 0.0057881, 0.006634, 0.006634, 0.006634
|
||||
36, 0.028829, 0.012622, 0.0083021, 0.9495, 0.97817, 0.98928, 0.65483, 0.025652, 0.010463, 0.0067701, 0.006535, 0.006535, 0.006535
|
||||
37, 0.028152, 0.012452, 0.008016, 0.95411, 0.98699, 0.99242, 0.74834, 0.029938, 0.010807, 0.0057073, 0.006436, 0.006436, 0.006436
|
||||
38, 0.028067, 0.0132, 0.0072333, 0.98131, 0.9871, 0.99342, 0.72968, 0.023942, 0.0098715, 0.0056729, 0.006337, 0.006337, 0.006337
|
||||
39, 0.02707, 0.012021, 0.0073622, 0.97159, 0.98606, 0.99106, 0.66866, 0.021726, 0.0096645, 0.0058436, 0.006238, 0.006238, 0.006238
|
||||
40, 0.025963, 0.012655, 0.0087835, 0.97675, 0.98624, 0.99053, 0.61778, 0.026124, 0.010141, 0.0056002, 0.006139, 0.006139, 0.006139
|
||||
41, 0.025687, 0.01183, 0.0075706, 0.88505, 0.98679, 0.99024, 0.74323, 0.025508, 0.0097275, 0.0051115, 0.00604, 0.00604, 0.00604
|
||||
42, 0.026962, 0.013543, 0.0070483, 0.98938, 0.98615, 0.99425, 0.79556, 0.019257, 0.0091076, 0.0049877, 0.005941, 0.005941, 0.005941
|
||||
43, 0.026752, 0.012546, 0.0073945, 0.99243, 0.97926, 0.99414, 0.82536, 0.020015, 0.0091324, 0.0050037, 0.005842, 0.005842, 0.005842
|
||||
44, 0.025512, 0.01291, 0.0065296, 0.99284, 0.98377, 0.99446, 0.8073, 0.022218, 0.0093803, 0.0047843, 0.005743, 0.005743, 0.005743
|
||||
45, 0.025071, 0.012273, 0.0064804, 0.92519, 0.98283, 0.99399, 0.8022, 0.022355, 0.0091429, 0.0051858, 0.005644, 0.005644, 0.005644
|
||||
46, 0.02441, 0.012031, 0.0067756, 0.9232, 0.98173, 0.95315, 0.81619, 0.019415, 0.0091877, 0.0052021, 0.005545, 0.005545, 0.005545
|
||||
47, 0.024003, 0.011556, 0.0061719, 0.9769, 0.98091, 0.99398, 0.79701, 0.018607, 0.0089998, 0.0049653, 0.005446, 0.005446, 0.005446
|
||||
48, 0.023256, 0.013171, 0.0057394, 0.98993, 0.97992, 0.99348, 0.79191, 0.023383, 0.0096035, 0.0049262, 0.005347, 0.005347, 0.005347
|
||||
49, 0.022691, 0.01123, 0.0064885, 0.96746, 0.98329, 0.99362, 0.80438, 0.020979, 0.0090265, 0.0046365, 0.005248, 0.005248, 0.005248
|
||||
50, 0.023009, 0.010828, 0.0061525, 0.97973, 0.9809, 0.99406, 0.78401, 0.021838, 0.009346, 0.0045595, 0.005149, 0.005149, 0.005149
|
||||
51, 0.022762, 0.011628, 0.0055389, 0.98075, 0.97948, 0.99472, 0.79553, 0.020373, 0.0091763, 0.0044677, 0.00505, 0.00505, 0.00505
|
||||
52, 0.022359, 0.011327, 0.0064108, 0.92924, 0.97627, 0.99434, 0.82906, 0.01873, 0.0088215, 0.0047634, 0.004951, 0.004951, 0.004951
|
||||
53, 0.021434, 0.010782, 0.0063598, 0.89751, 0.98395, 0.99438, 0.82292, 0.01758, 0.0084286, 0.0047634, 0.004852, 0.004852, 0.004852
|
||||
54, 0.021491, 0.011245, 0.0060554, 0.93484, 0.9871, 0.99439, 0.76245, 0.019861, 0.0091343, 0.0045495, 0.004753, 0.004753, 0.004753
|
||||
55, 0.02136, 0.010731, 0.005393, 0.98175, 0.97451, 0.99376, 0.81609, 0.017771, 0.0085478, 0.0044975, 0.004654, 0.004654, 0.004654
|
||||
56, 0.020601, 0.011435, 0.0048984, 0.98702, 0.97619, 0.99379, 0.77352, 0.020876, 0.0089264, 0.0044127, 0.004555, 0.004555, 0.004555
|
||||
57, 0.020204, 0.01007, 0.0049571, 0.98484, 0.97553, 0.99377, 0.80822, 0.018683, 0.0087328, 0.0042574, 0.004456, 0.004456, 0.004456
|
||||
58, 0.020187, 0.010405, 0.0048422, 0.99255, 0.97817, 0.99174, 0.77373, 0.018314, 0.0085936, 0.0043662, 0.004357, 0.004357, 0.004357
|
||||
59, 0.019939, 0.011237, 0.0055137, 0.96766, 0.98313, 0.99227, 0.79108, 0.018299, 0.0086794, 0.0046237, 0.004258, 0.004258, 0.004258
|
||||
60, 0.019841, 0.010175, 0.0051564, 0.97467, 0.98512, 0.99305, 0.83424, 0.016635, 0.008214, 0.0044363, 0.004159, 0.004159, 0.004159
|
||||
61, 0.019577, 0.011111, 0.0053072, 0.98888, 0.9871, 0.99366, 0.84728, 0.018191, 0.0086145, 0.0041327, 0.00406, 0.00406, 0.00406
|
||||
62, 0.020016, 0.0097929, 0.0057736, 0.98464, 0.9871, 0.99353, 0.81056, 0.016411, 0.0081959, 0.0042267, 0.003961, 0.003961, 0.003961
|
||||
63, 0.018354, 0.010467, 0.0048361, 0.99336, 0.9851, 0.99354, 0.78057, 0.017278, 0.0084858, 0.0038996, 0.003862, 0.003862, 0.003862
|
||||
64, 0.019343, 0.010997, 0.0050088, 0.99232, 0.98663, 0.99367, 0.83564, 0.016815, 0.0083208, 0.0038519, 0.003763, 0.003763, 0.003763
|
||||
65, 0.018261, 0.0098814, 0.0060664, 0.98882, 0.9871, 0.99358, 0.82697, 0.015722, 0.0081091, 0.0038631, 0.003664, 0.003664, 0.003664
|
||||
66, 0.017361, 0.010034, 0.0045755, 0.9908, 0.9871, 0.99353, 0.86476, 0.014229, 0.0077305, 0.0040259, 0.003565, 0.003565, 0.003565
|
||||
67, 0.018567, 0.010758, 0.0043478, 0.99195, 0.9871, 0.9936, 0.86666, 0.013242, 0.0076628, 0.0036473, 0.003466, 0.003466, 0.003466
|
||||
68, 0.017044, 0.010896, 0.004663, 0.99249, 0.98488, 0.99403, 0.84897, 0.015298, 0.0079508, 0.0035157, 0.003367, 0.003367, 0.003367
|
||||
69, 0.016631, 0.0092014, 0.0043957, 0.98846, 0.98422, 0.99374, 0.81506, 0.015467, 0.0079451, 0.0035839, 0.003268, 0.003268, 0.003268
|
||||
70, 0.01695, 0.010094, 0.0035115, 0.99048, 0.98446, 0.99367, 0.84357, 0.014905, 0.0078063, 0.0035594, 0.003169, 0.003169, 0.003169
|
||||
71, 0.015838, 0.010228, 0.003958, 0.99303, 0.98292, 0.99246, 0.90626, 0.012365, 0.0071888, 0.0033793, 0.00307, 0.00307, 0.00307
|
||||
72, 0.015778, 0.0095427, 0.0062521, 0.99223, 0.98173, 0.99247, 0.85636, 0.014819, 0.0079422, 0.0033822, 0.002971, 0.002971, 0.002971
|
||||
73, 0.015479, 0.0093237, 0.00404, 0.99072, 0.98312, 0.99374, 0.86208, 0.015422, 0.0078058, 0.0033088, 0.002872, 0.002872, 0.002872
|
||||
74, 0.015936, 0.0093511, 0.0045926, 0.98964, 0.98485, 0.99389, 0.87519, 0.012562, 0.0072331, 0.0032785, 0.002773, 0.002773, 0.002773
|
||||
75, 0.014587, 0.0090074, 0.0044003, 0.98713, 0.9871, 0.99287, 0.88673, 0.013244, 0.0074663, 0.0034659, 0.002674, 0.002674, 0.002674
|
||||
76, 0.014562, 0.0085611, 0.003786, 0.98725, 0.9871, 0.99325, 0.86882, 0.012914, 0.007401, 0.0032434, 0.002575, 0.002575, 0.002575
|
||||
77, 0.014627, 0.0093808, 0.0040065, 0.98718, 0.9871, 0.99327, 0.85954, 0.013101, 0.0073853, 0.003063, 0.002476, 0.002476, 0.002476
|
||||
78, 0.014713, 0.0086822, 0.0041137, 0.98856, 0.98458, 0.99338, 0.85969, 0.013281, 0.0073719, 0.0029892, 0.002377, 0.002377, 0.002377
|
||||
79, 0.013479, 0.008951, 0.0032, 0.99063, 0.98275, 0.99299, 0.89536, 0.011977, 0.0070486, 0.0029796, 0.002278, 0.002278, 0.002278
|
||||
80, 0.01334, 0.0088546, 0.0039412, 0.99078, 0.98297, 0.99239, 0.90339, 0.011971, 0.0071206, 0.0030048, 0.002179, 0.002179, 0.002179
|
||||
81, 0.013471, 0.0085181, 0.0038238, 0.99147, 0.98339, 0.99223, 0.9112, 0.011377, 0.0070229, 0.0029151, 0.00208, 0.00208, 0.00208
|
||||
82, 0.013225, 0.0081305, 0.0039529, 0.98983, 0.98394, 0.99189, 0.90095, 0.011049, 0.0069065, 0.0028324, 0.001981, 0.001981, 0.001981
|
||||
83, 0.012782, 0.0087502, 0.0041046, 0.98948, 0.98345, 0.99231, 0.87987, 0.011397, 0.0071707, 0.0028323, 0.001882, 0.001882, 0.001882
|
||||
84, 0.01268, 0.008468, 0.003646, 0.98967, 0.98255, 0.99349, 0.90452, 0.010897, 0.0069289, 0.0028338, 0.001783, 0.001783, 0.001783
|
||||
85, 0.011956, 0.0081656, 0.0033978, 0.99234, 0.98695, 0.99349, 0.90359, 0.011106, 0.0069551, 0.0027155, 0.001684, 0.001684, 0.001684
|
||||
86, 0.011678, 0.0074737, 0.0029689, 0.99059, 0.9871, 0.99331, 0.90539, 0.011038, 0.0070376, 0.0026494, 0.001585, 0.001585, 0.001585
|
||||
87, 0.011452, 0.0082765, 0.0031965, 0.99032, 0.9871, 0.99354, 0.90376, 0.011192, 0.0070019, 0.0026226, 0.001486, 0.001486, 0.001486
|
||||
88, 0.011014, 0.0077558, 0.0029091, 0.98926, 0.9871, 0.99367, 0.93096, 0.0097374, 0.0064735, 0.0025889, 0.001387, 0.001387, 0.001387
|
||||
89, 0.010877, 0.0081713, 0.0035058, 0.98853, 0.9871, 0.99369, 0.89844, 0.010716, 0.0067215, 0.0025122, 0.001288, 0.001288, 0.001288
|
||||
90, 0.01086, 0.0081078, 0.0029808, 0.98859, 0.9871, 0.99369, 0.90179, 0.010313, 0.0066843, 0.002467, 0.001189, 0.001189, 0.001189
|
||||
91, 0.010432, 0.0082593, 0.0032532, 0.98823, 0.98823, 0.99386, 0.90426, 0.00942, 0.0063066, 0.0025923, 0.00109, 0.00109, 0.00109
|
||||
92, 0.0099856, 0.0072484, 0.0027239, 0.98621, 0.98861, 0.99381, 0.91917, 0.010086, 0.0064635, 0.0026085, 0.000991, 0.000991, 0.000991
|
||||
93, 0.0097199, 0.0081254, 0.0029498, 0.98445, 0.98366, 0.99358, 0.92386, 0.0092925, 0.0062866, 0.0023818, 0.000892, 0.000892, 0.000892
|
||||
94, 0.0098492, 0.0087202, 0.0028662, 0.98588, 0.98249, 0.99359, 0.92486, 0.0095873, 0.0064139, 0.0023302, 0.000793, 0.000793, 0.000793
|
||||
95, 0.0095458, 0.0077495, 0.0031524, 0.98675, 0.98195, 0.99366, 0.91152, 0.0091509, 0.0061636, 0.002304, 0.000694, 0.000694, 0.000694
|
||||
96, 0.0093134, 0.0070511, 0.010882, 0.98633, 0.98247, 0.99361, 0.91815, 0.0090792, 0.0062695, 0.0022655, 0.000595, 0.000595, 0.000595
|
||||
97, 0.0092242, 0.0074598, 0.0032303, 0.98604, 0.98365, 0.99366, 0.9308, 0.0082706, 0.005929, 0.0022603, 0.000496, 0.000496, 0.000496
|
||||
98, 0.0088322, 0.007461, 0.0025581, 0.9797, 0.9832, 0.99359, 0.92623, 0.0086755, 0.006093, 0.0023018, 0.000397, 0.000397, 0.000397
|
||||
99, 0.009008, 0.0076601, 0.0027773, 0.97461, 0.98322, 0.99354, 0.93797, 0.0082771, 0.0060029, 0.0023297, 0.000298, 0.000298, 0.000298
|
||||
|
BIN
models/weights/results.png
Normal file
BIN
models/weights/results.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 260 KiB |
BIN
models/weights/train_batch0.jpg
Normal file
BIN
models/weights/train_batch0.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 265 KiB |
BIN
models/weights/train_batch1.jpg
Normal file
BIN
models/weights/train_batch1.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 259 KiB |
BIN
models/weights/train_batch2.jpg
Normal file
BIN
models/weights/train_batch2.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 251 KiB |
BIN
models/weights/val_batch0_labels.jpg
Normal file
BIN
models/weights/val_batch0_labels.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 276 KiB |
BIN
models/weights/val_batch0_pred.jpg
Normal file
BIN
models/weights/val_batch0_pred.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 299 KiB |
BIN
models/weights/val_batch1_labels.jpg
Normal file
BIN
models/weights/val_batch1_labels.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 273 KiB |
BIN
models/weights/val_batch1_pred.jpg
Normal file
BIN
models/weights/val_batch1_pred.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 295 KiB |
@@ -9,7 +9,7 @@ import os
|
||||
import sys
|
||||
import time
|
||||
import json
|
||||
import yaml # 新增导入
|
||||
import yaml
|
||||
import argparse
|
||||
import logging
|
||||
import random
|
||||
@@ -215,12 +215,15 @@ class DNFDataCollector:
|
||||
return count
|
||||
|
||||
def create_dataset_config(self):
|
||||
"""创建YOLO数据集配置文件"""
|
||||
"""创建YOLO数据集配置文件（修复版）"""
|
||||
data_yaml_path = self.output_dir / "data.yaml"
|
||||
|
||||
# 数据集配置
|
||||
# 使用绝对路径
|
||||
abs_data_dir = self.output_dir.absolute()
|
||||
|
||||
# 确保路径正确，YOLOv5期望的格式
|
||||
data_config = {
|
||||
"path": str(self.output_dir.absolute()),
|
||||
"path": str(abs_data_dir),
|
||||
"train": str((self.images_dir / "train").absolute()),
|
||||
"val": str((self.images_dir / "val").absolute()),
|
||||
"test": str((self.images_dir / "test").absolute()),
|
||||
|
||||
@@ -37,7 +37,7 @@ class YOLOTrainer:
|
||||
self.config = self.load_config()
|
||||
|
||||
# YOLO仓库路径
|
||||
self.yolo_repo = Path(self.config.get("yolo_repo", "yolov5"))
|
||||
self.yolo_repo = Path(self.config.get("yolo_repo", "tools/yolov5"))
|
||||
|
||||
# 检查配置
|
||||
self.validate_config()
|
||||
@@ -82,44 +82,24 @@ class YOLOTrainer:
|
||||
logger.error(f"数据目录不存在: {data_dir}")
|
||||
return False
|
||||
|
||||
# 创建YOLO数据配置
|
||||
data_yaml_path = data_dir / "data.yaml"
|
||||
# 验证数据目录结构
|
||||
images_dir = data_dir / "images"
|
||||
train_dir = images_dir / "train"
|
||||
val_dir = images_dir / "val"
|
||||
|
||||
if not train_dir.exists() or not val_dir.exists():
|
||||
logger.warning(f"训练/验证目录不存在: {train_dir} / {val_dir}")
|
||||
logger.warning("请先运行 data_collector.py 生成训练数据")
|
||||
return False
|
||||
|
||||
# 统计图像数量
|
||||
images_dir = data_dir / "images"
|
||||
train_images = list((images_dir / "train").glob("*.jpg"))
|
||||
val_images = list((images_dir / "val").glob("*.jpg"))
|
||||
train_images = list(train_dir.glob("*.jpg"))
|
||||
val_images = list(val_dir.glob("*.jpg"))
|
||||
|
||||
if not train_images:
|
||||
logger.warning(f"没有找到训练图像: {images_dir / 'train'}")
|
||||
|
||||
if not val_images:
|
||||
logger.warning(f"没有找到验证图像: {images_dir / 'val'}")
|
||||
|
||||
# 获取类别
|
||||
classes = self.config.get("classes", [
|
||||
"monster", "boss", "door", "item", "npc", "player",
|
||||
"hp_bar", "mp_bar", "skill_ready", "cooldown"
|
||||
])
|
||||
|
||||
# 创建数据配置文件
|
||||
data_config = {
|
||||
"path": str(data_dir),
|
||||
"train": str(images_dir / "train"),
|
||||
"val": str(images_dir / "val"),
|
||||
"test": str(images_dir / "test"),
|
||||
"nc": len(classes),
|
||||
"names": classes
|
||||
}
|
||||
|
||||
# 保存配置
|
||||
with open(data_yaml_path, "w", encoding="utf-8") as f:
|
||||
yaml.dump(data_config, f, default_flow_style=False, sort_keys=False)
|
||||
|
||||
logger.info(f"已创建数据配置: {data_yaml_path}")
|
||||
logger.info(f"已创建数据配置: {data_dir / 'data.yaml'}")
|
||||
logger.info(f"训练图像: {len(train_images)}, 验证图像: {len(val_images)}")
|
||||
|
||||
return True
|
||||
return len(train_images) > 0 and len(val_images) > 0
|
||||
|
||||
def clone_yolo_repo(self):
|
||||
"""克隆YOLOv5仓库"""
|
||||
|
||||
Reference in New Issue
Block a user