Initial commit: Recycling object detection project

- Added Fast api web application for recycling object detection
- Included YOLOv8 model training notebook
- Set up project structure with datasets and training directories
- Added requirements.txt for dependencies
- Configured .gitignore for Python virtual environment and cache files
This commit is contained in:
boladeE
2025-04-23 19:18:05 +01:00
commit a6e52f8ad0
454 changed files with 2649 additions and 0 deletions
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task: detect
mode: train
model: yolov8n.pt
data: c:\Users\babaw\Documents\Work\Mana Knight Digital\ds_task_recycling_project\datasets\data.yaml
epochs: 50
time: null
patience: 100
batch: 16
imgsz: 640
save: true
save_period: -1
cache: false
device: null
workers: 8
project: null
name: train7
exist_ok: false
pretrained: true
optimizer: auto
verbose: true
seed: 0
deterministic: true
single_cls: false
rect: false
cos_lr: false
close_mosaic: 10
resume: false
amp: true
fraction: 1.0
profile: false
freeze: null
multi_scale: false
overlap_mask: true
mask_ratio: 4
dropout: 0.0
val: true
split: val
save_json: false
conf: null
iou: 0.7
max_det: 300
half: false
dnn: false
plots: true
source: null
vid_stride: 1
stream_buffer: false
visualize: false
augment: false
agnostic_nms: false
classes: null
retina_masks: false
embed: null
show: false
save_frames: false
save_txt: false
save_conf: false
save_crop: false
show_labels: true
show_conf: true
show_boxes: true
line_width: null
format: torchscript
keras: false
optimize: false
int8: false
dynamic: false
simplify: true
opset: null
workspace: null
nms: false
lr0: 0.01
lrf: 0.01
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5
cls: 0.5
dfl: 1.5
pose: 12.0
kobj: 1.0
nbs: 64
hsv_h: 0.015
hsv_s: 0.7
hsv_v: 0.4
degrees: 0.0
translate: 0.1
scale: 0.5
shear: 0.0
perspective: 0.0
flipud: 0.0
fliplr: 0.5
bgr: 0.0
mosaic: 1.0
mixup: 0.0
copy_paste: 0.0
copy_paste_mode: flip
auto_augment: randaugment
erasing: 0.4
cfg: null
tracker: botsort.yaml
save_dir: c:\Users\babaw\Documents\Work\Mana Knight Digital\ds_task_recycling_project\datasets\runs\detect\train7
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epoch,time,train/box_loss,train/cls_loss,train/dfl_loss,metrics/precision(B),metrics/recall(B),metrics/mAP50(B),metrics/mAP50-95(B),val/box_loss,val/cls_loss,val/dfl_loss,lr/pg0,lr/pg1,lr/pg2
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16,909.287,1.04644,0.8167,1.14854,0.77532,0.71927,0.79227,0.50756,1.30848,1.29365,1.53777,0.001406,0.001406,0.001406
17,973.886,1.05134,0.8072,1.15606,0.77957,0.58971,0.67932,0.39674,1.43737,1.38893,1.62843,0.0013664,0.0013664,0.0013664
18,1038.19,1.01895,0.76075,1.12363,0.75585,0.75,0.79299,0.54014,1.19492,1.06695,1.43887,0.0013268,0.0013268,0.0013268
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21,1235.9,0.97969,0.72155,1.10969,0.87089,0.79167,0.87398,0.49915,1.61727,0.97409,1.8339,0.001208,0.001208,0.001208
22,1301.63,0.96498,0.69427,1.08961,0.82713,0.59862,0.8583,0.44535,1.49811,0.94941,1.6617,0.0011684,0.0011684,0.0011684
23,1375.05,0.97176,0.69995,1.12122,0.98851,0.5,0.70735,0.36377,1.45452,0.90547,1.56864,0.0011288,0.0011288,0.0011288
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45,3030.88,0.66399,0.48501,0.96783,0.86873,0.875,0.94374,0.5493,1.37376,0.62126,1.76597,0.0002576,0.0002576,0.0002576
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1 epoch time train/box_loss train/cls_loss train/dfl_loss metrics/precision(B) metrics/recall(B) metrics/mAP50(B) metrics/mAP50-95(B) val/box_loss val/cls_loss val/dfl_loss lr/pg0 lr/pg1 lr/pg2
2 1 54.2497 2.06475 3.28559 1.98692 0.01333 1 0.33729 0.17014 1.93235 2.90451 1.84283 0.00018 0.00018 0.00018
3 2 105.789 1.60795 1.73886 1.42903 0.04429 0.70833 0.6133 0.31939 1.85374 2.44436 1.72346 0.000372476 0.000372476 0.000372476
4 3 157.32 1.48166 1.39392 1.33944 0.01333 1 0.58472 0.19178 1.72844 2.89381 1.78894 0.000557032 0.000557032 0.000557032
5 4 208.774 1.34582 1.22969 1.27148 0.01333 1 0.6083 0.19769 2.02742 2.67312 1.90923 0.000733668 0.000733668 0.000733668
6 5 263.416 1.29696 1.1387 1.27776 0.01167 0.875 0.32824 0.12628 1.80957 2.9277 1.93331 0.000902384 0.000902384 0.000902384
7 6 316.659 1.32609 1.19217 1.29891 1 0.32314 0.55136 0.25631 1.65501 2.36249 1.66467 0.00106318 0.00106318 0.00106318
8 7 370.237 1.26765 1.09562 1.27424 0.83303 0.41585 0.55229 0.28987 1.64476 2.14156 1.65976 0.00121606 0.00121606 0.00121606
9 8 424.139 1.24118 1.02811 1.21346 1 0.23779 0.31152 0.1936 1.53292 2.41104 1.74351 0.00136101 0.00136101 0.00136101
10 9 479.369 1.2307 1.01492 1.21561 0.87007 0.28016 0.40512 0.23051 1.60375 2.01821 1.85871 0.00149805 0.00149805 0.00149805
11 10 538.627 1.25632 1.07046 1.25763 0.73801 0.375 0.45316 0.25944 1.55876 2.01301 1.83093 0.00162716 0.00162716 0.00162716
12 11 596.26 1.19315 1.0017 1.23698 0.94133 0.45833 0.616 0.37669 1.54146 1.88414 1.79534 0.001604 0.001604 0.001604
13 12 655.016 1.21302 0.95347 1.25888 0.87584 0.41667 0.50074 0.25638 1.75181 2.02174 1.98871 0.0015644 0.0015644 0.0015644
14 13 715.277 1.15439 0.91539 1.20183 1 0.57733 0.74564 0.37953 1.8085 1.333 1.96653 0.0015248 0.0015248 0.0015248
15 14 777.134 1.09638 0.85925 1.16466 0.93632 0.70833 0.85861 0.49064 1.49037 0.94339 1.79087 0.0014852 0.0014852 0.0014852
16 15 843.665 1.05888 0.81842 1.15457 0.76475 0.70833 0.83217 0.52387 1.47243 0.98751 1.76234 0.0014456 0.0014456 0.0014456
17 16 909.287 1.04644 0.8167 1.14854 0.77532 0.71927 0.79227 0.50756 1.30848 1.29365 1.53777 0.001406 0.001406 0.001406
18 17 973.886 1.05134 0.8072 1.15606 0.77957 0.58971 0.67932 0.39674 1.43737 1.38893 1.62843 0.0013664 0.0013664 0.0013664
19 18 1038.19 1.01895 0.76075 1.12363 0.75585 0.75 0.79299 0.54014 1.19492 1.06695 1.43887 0.0013268 0.0013268 0.0013268
20 19 1102.59 0.99528 0.74277 1.10987 0.84396 0.70833 0.80284 0.5417 1.26264 0.86554 1.50366 0.0012872 0.0012872 0.0012872
21 20 1169.64 1.02288 0.74384 1.13908 0.92166 0.79167 0.89138 0.42992 1.82014 0.95111 2.05613 0.0012476 0.0012476 0.0012476
22 21 1235.9 0.97969 0.72155 1.10969 0.87089 0.79167 0.87398 0.49915 1.61727 0.97409 1.8339 0.001208 0.001208 0.001208
23 22 1301.63 0.96498 0.69427 1.08961 0.82713 0.59862 0.8583 0.44535 1.49811 0.94941 1.6617 0.0011684 0.0011684 0.0011684
24 23 1375.05 0.97176 0.69995 1.12122 0.98851 0.5 0.70735 0.36377 1.45452 0.90547 1.56864 0.0011288 0.0011288 0.0011288
25 24 1483 0.93529 0.66614 1.09092 1 0.78404 0.92018 0.52713 1.26578 0.81984 1.39338 0.0010892 0.0010892 0.0010892
26 25 1570.57 0.94593 0.67634 1.09923 1 0.82488 0.93674 0.51259 1.43898 0.95183 1.44066 0.0010496 0.0010496 0.0010496
27 26 1640.5 0.9005 0.64656 1.08853 0.85685 0.79167 0.87822 0.59599 1.00997 0.74692 1.25779 0.00101 0.00101 0.00101
28 27 1716.79 0.88047 0.65839 1.0819 0.98302 0.66667 0.79722 0.47007 1.44935 0.90317 1.58064 0.0009704 0.0009704 0.0009704
29 28 1790.17 0.92727 0.6491 1.07941 0.96438 0.79167 0.88789 0.51198 1.41082 0.95921 1.55489 0.0009308 0.0009308 0.0009308
30 29 1863.25 0.86808 0.61314 1.06347 1 0.73943 0.85062 0.53272 1.26679 0.77515 1.5057 0.0008912 0.0008912 0.0008912
31 30 1935.03 0.85237 0.60318 1.03757 0.86759 0.81945 0.90299 0.56004 1.32215 0.70391 1.68444 0.0008516 0.0008516 0.0008516
32 31 2006.05 0.85848 0.59069 1.04725 0.91204 0.86446 0.93329 0.61701 1.22052 0.70212 1.53785 0.000812 0.000812 0.000812
33 32 2074.85 0.8607 0.60328 1.06674 0.99448 0.83333 0.96865 0.58854 1.34406 0.70627 1.61132 0.0007724 0.0007724 0.0007724
34 33 2146.12 0.81712 0.57815 1.03472 0.94911 0.91667 0.94354 0.57918 1.23064 0.65719 1.46887 0.0007328 0.0007328 0.0007328
35 34 2215.61 0.82113 0.56747 1.03675 0.98124 0.75 0.8458 0.43565 1.65251 0.69818 1.86693 0.0006932 0.0006932 0.0006932
36 35 2283.46 0.80104 0.57305 1.02593 0.9542 0.86835 0.90976 0.48068 1.43441 0.64857 1.70736 0.0006536 0.0006536 0.0006536
37 36 2362.48 0.83103 0.57551 1.03499 0.87273 0.85758 0.9038 0.44998 1.5691 0.69063 1.97723 0.000614 0.000614 0.000614
38 37 2432.12 0.80527 0.56112 1.02551 0.80806 0.87714 0.90845 0.47423 1.51444 0.64712 1.89872 0.0005744 0.0005744 0.0005744
39 38 2508.79 0.7726 0.55171 1.01768 0.89864 0.79167 0.89273 0.51093 1.3883 0.59906 1.7624 0.0005348 0.0005348 0.0005348
40 39 2577.65 0.7675 0.53945 1.00972 0.83538 0.83333 0.91731 0.51633 1.4967 0.65808 1.87353 0.0004952 0.0004952 0.0004952
41 40 2648.26 0.76832 0.54621 1.01197 0.9061 0.83333 0.92334 0.49587 1.6318 0.72062 1.97779 0.0004556 0.0004556 0.0004556
42 41 2723.96 0.69593 0.54869 0.98187 0.95342 0.875 0.91278 0.46972 1.66482 0.70379 2.11677 0.000416 0.000416 0.000416
43 42 2803 0.71207 0.53965 0.99659 0.95001 0.83333 0.85669 0.46264 1.56204 0.65859 2.0364 0.0003764 0.0003764 0.0003764
44 43 2877.49 0.69033 0.51838 0.98369 0.95411 0.86665 0.92135 0.49602 1.5114 0.65125 1.90967 0.0003368 0.0003368 0.0003368
45 44 2955.03 0.67106 0.49273 0.97654 0.92953 0.75 0.888 0.47663 1.56378 0.62817 1.96979 0.0002972 0.0002972 0.0002972
46 45 3030.88 0.66399 0.48501 0.96783 0.86873 0.875 0.94374 0.5493 1.37376 0.62126 1.76597 0.0002576 0.0002576 0.0002576
47 46 3201.5 0.66717 0.48721 0.9668 0.87544 0.91667 0.9293 0.53737 1.33496 0.61767 1.70695 0.000218 0.000218 0.000218
48 47 3262.79 0.63017 0.47082 0.96586 0.94224 0.875 0.95991 0.50304 1.41911 0.62492 1.79879 0.0001784 0.0001784 0.0001784
49 48 3324.62 0.63678 0.47311 0.95304 0.98764 0.79167 0.90331 0.49543 1.4591 0.63498 1.87332 0.0001388 0.0001388 0.0001388
50 49 3387.48 0.63551 0.46808 0.931 0.88336 0.94704 0.93836 0.53024 1.40884 0.61606 1.80694 9.92e-05 9.92e-05 9.92e-05
51 50 3457.88 0.60539 0.45653 0.94608 0.91257 0.87003 0.90122 0.50731 1.39162 0.61616 1.78099 5.96e-05 5.96e-05 5.96e-05
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