add cheque model

.gitattributes

@@ -33,3 +33,22 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/confusion_matrix_normalized.png filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/confusion_matrix.png filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/F1_curve.png filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/labels_correlogram.jpg filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/labels.jpg filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/P_curve.png filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/PR_curve.png filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/R_curve.png filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/results.png filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/train_batch0.jpg filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/train_batch1.jpg filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/train_batch2.jpg filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/train_batch660.jpg filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/train_batch661.jpg filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/train_batch662.jpg filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/val_batch0_labels.jpg filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/val_batch0_pred.jpg filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/val_batch1_labels.jpg filter=lfs diff=lfs merge=lfs -text
+cheque-yolo/train/val_batch1_pred.jpg filter=lfs diff=lfs merge=lfs -text

cheque-yolo/my_model.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f7a054e8b6ae1e30f188e46498cd30132f2993f91da4d3b4bc31d84d971b98d1
+size 19147219

cheque-yolo/train/args.yaml

@@ -0,0 +1,106 @@
+task: detect
+mode: train
+model: yolo11s.pt
+data: /content/data.yaml
+epochs: 40
+time: null
+patience: 100
+batch: 16
+imgsz: 640
+save: true
+save_period: -1
+cache: false
+device: null
+workers: 8
+project: null
+name: train
+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
+save_hybrid: 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
+crop_fraction: 1.0
+cfg: null
+tracker: botsort.yaml
+save_dir: runs/detect/train

cheque-yolo/train/events.out.tfevents.1740405995.6b8cd8797859.5746.0

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cdc5cead03ecdd8d3bec6ac14f6c442463b1e44466902d894a0e7eaf12092254
+size 298190

cheque-yolo/train/results.csv

@@ -0,0 +1,41 @@
+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
+1,15.8148,1.33856,3.05038,1.51175,0.52233,0.72895,0.74418,0.45927,1.28563,3.59651,1.37062,0.00030009,0.00030009,0.00030009
+2,25.3435,0.63234,0.89597,1.02932,0.38184,0.82885,0.49431,0.17361,2.5735,10.055,3.53692,0.000599262,0.000599262,0.000599262
+3,33.7574,0.67617,0.81387,1.07087,0.8658,0.91121,0.93381,0.74203,0.83055,1.15438,1.0342,0.000882872,0.000882872,0.000882872
+4,42.3735,0.67765,0.67574,1.07353,0.34722,0.63551,0.3892,0.23781,1.37283,2.36549,1.48622,0.00115092,0.00115092,0.00115092
+5,51.2122,0.66597,0.63354,1.0652,0.56695,0.69732,0.6763,0.31157,1.80743,2.64211,2.18595,0.00128753,0.00128753,0.00128753
+6,58.8012,0.63892,0.61218,1.04725,0.80983,0.8023,0.8694,0.56022,1.27934,1.53787,1.27919,0.00125216,0.00125216,0.00125216
+7,67.5556,0.59878,0.54899,1.02489,0.57635,0.78255,0.67381,0.40147,1.54922,2.05303,1.75594,0.00121679,0.00121679,0.00121679
+8,75.8391,0.61992,0.57604,1.03994,0.40283,0.81394,0.66509,0.39464,1.5202,2.30423,1.35208,0.00118143,0.00118143,0.00118143
+9,84.0169,0.58221,0.53353,1.01883,0.75108,0.87137,0.93059,0.63467,1.00893,1.16059,0.99725,0.00114606,0.00114606,0.00114606
+10,92.9418,0.57551,0.53781,1.00886,0.75757,0.66182,0.89871,0.72691,1.08849,1.42835,1.35892,0.00111069,0.00111069,0.00111069
+11,100.755,0.53814,0.47489,0.96455,0.76024,0.80684,0.85204,0.64817,1.01844,1.36517,1.10136,0.00107532,0.00107532,0.00107532
+12,109.625,0.52385,0.45721,0.97729,0.74594,0.62973,0.78105,0.63753,1.23309,1.12283,1.39364,0.00103995,0.00103995,0.00103995
+13,118.034,0.48807,0.47279,0.95345,0.8814,0.92721,0.9621,0.83003,0.56597,0.59756,0.72321,0.00100459,0.00100459,0.00100459
+14,126.261,0.45999,0.39217,0.95261,0.89953,0.96491,0.96524,0.79064,0.62571,0.63536,0.86196,0.000969219,0.000969219,0.000969219
+15,135.161,0.51995,0.4275,0.97653,0.96544,0.94522,0.9594,0.81507,0.64376,0.48963,0.78141,0.000933851,0.000933851,0.000933851
+16,142.752,0.4887,0.413,0.95864,0.8902,0.96491,0.95892,0.81472,0.56674,0.45028,0.68534,0.000898484,0.000898484,0.000898484
+17,151.565,0.49164,0.41122,0.96253,0.91999,0.96491,0.96106,0.83779,0.5656,0.44556,0.71639,0.000863116,0.000863116,0.000863116
+18,160.196,0.49252,0.40819,0.97224,0.9528,0.96186,0.95572,0.80326,0.57595,0.39678,0.6965,0.000827748,0.000827748,0.000827748
+19,168.199,0.4824,0.39369,0.94852,0.87792,0.96491,0.95848,0.76824,0.76194,0.61658,0.9306,0.00079238,0.00079238,0.00079238
+20,177.086,0.46342,0.38484,0.95627,0.98603,0.96491,0.96402,0.83329,0.50527,0.37195,0.67222,0.000757013,0.000757013,0.000757013
+21,184.783,0.46228,0.36811,0.94019,0.94705,0.96491,0.96454,0.84388,0.48932,0.34778,0.63737,0.000721645,0.000721645,0.000721645
+22,193.663,0.44594,0.36323,0.92601,0.90864,0.96491,0.96063,0.84892,0.4276,0.36736,0.61658,0.000686277,0.000686277,0.000686277
+23,202.232,0.46154,0.3579,0.94439,0.96549,0.96491,0.97772,0.87307,0.44801,0.31059,0.6319,0.000650909,0.000650909,0.000650909
+24,210.394,0.45559,0.34665,0.95315,0.97464,0.96491,0.96567,0.84056,0.5127,0.28579,0.64989,0.000615542,0.000615542,0.000615542
+25,219.216,0.43186,0.33438,0.93626,0.9778,0.96491,0.96503,0.83975,0.55874,0.32022,0.71104,0.000580174,0.000580174,0.000580174
+26,226.979,0.43727,0.34009,0.9268,0.94566,0.96491,0.96485,0.84798,0.53143,0.33021,0.70804,0.000544806,0.000544806,0.000544806
+27,235.61,0.41034,0.3054,0.92455,0.98338,0.96491,0.96523,0.86471,0.47397,0.25075,0.64895,0.000509438,0.000509438,0.000509438
+28,244.417,0.42425,0.31841,0.91788,0.96807,0.96491,0.96438,0.84453,0.47136,0.29258,0.64182,0.000474071,0.000474071,0.000474071
+29,252.423,0.40588,0.30509,0.91475,0.9721,0.96491,0.9638,0.84945,0.4882,0.31749,0.64763,0.000438703,0.000438703,0.000438703
+30,261.405,0.41739,0.30362,0.93157,0.96611,0.96491,0.96308,0.85421,0.50931,0.33335,0.65627,0.000403335,0.000403335,0.000403335
+31,271.249,0.41723,0.47701,0.92433,0.9563,0.96491,0.95949,0.845,0.48471,0.37715,0.6649,0.000367967,0.000367967,0.000367967
+32,279.509,0.40981,0.29707,0.91639,0.97673,0.96491,0.96622,0.85311,0.48827,0.32176,0.63669,0.0003326,0.0003326,0.0003326
+33,288.385,0.39352,0.28043,0.89801,0.97906,0.96491,0.96622,0.83988,0.44963,0.30769,0.6354,0.000297232,0.000297232,0.000297232
+34,295.944,0.40773,0.28854,0.90381,0.98285,0.96491,0.96669,0.84719,0.4233,0.29203,0.62699,0.000261864,0.000261864,0.000261864
+35,304.58,0.4101,0.26627,0.91441,0.98374,0.96491,0.98094,0.86483,0.40062,0.28641,0.64552,0.000226497,0.000226497,0.000226497
+36,312.79,0.38208,0.27905,0.89334,0.98399,0.96491,0.97656,0.85228,0.3972,0.27885,0.62773,0.000191129,0.000191129,0.000191129
+37,320.976,0.38931,0.24952,0.89019,0.98086,0.96491,0.98143,0.84723,0.41101,0.26708,0.61308,0.000155761,0.000155761,0.000155761
+38,329.808,0.35866,0.24704,0.88562,0.98091,0.96491,0.98143,0.87148,0.39835,0.26542,0.61948,0.000120393,0.000120393,0.000120393
+39,337.416,0.37833,0.25184,0.87886,0.98071,0.96491,0.98163,0.87415,0.40951,0.26179,0.62035,8.50255e-05,8.50255e-05,8.50255e-05
+40,346.069,0.35825,0.23555,0.88831,0.98321,0.96491,0.98153,0.87515,0.38376,0.2608,0.6139,4.96578e-05,4.96578e-05,4.96578e-05

cheque-yolo/train/weights/best.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:f7a054e8b6ae1e30f188e46498cd30132f2993f91da4d3b4bc31d84d971b98d1
+size 19147219

cheque-yolo/train/weights/last.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:938222257695e3c1ae375ab11a3466902875d3167c61dbec532e3526c18d5467
+size 19147219