diff --git a/README.md b/README.md index e69de29..710162e 100644 --- a/README.md +++ b/README.md @@ -0,0 +1,58 @@ +# 지능화 캡스톤 프로젝트 #2 - YOLOv5 안전모 검출 + +----- + + +[PINBlog Gitea Repository](https://gitea.pinblog.codes/CBNU/19_YOLOv5) +* 제출했던 프로젝트 코드가 날라가서 일부만 존재함;; + +----- + +### YOLOv5 GitHub +[YOLOv5](https://github.com/ultralytics/yolov5) + + +# 프로젝트 목표 +* YOLOv5 모델을 학습하여 영상의 안전모와 마스크를 검출 + +# 구현 방법 +* 일반적인 1개의 모델로 여러 클래스를 학습하지 않고, Detect Model로 머리를 검출하여 ROI 취득 후, +해당 ROI를 Crop하여 Classification Model로 안전모, 마스크, 미착용 등을 분류한다. + +# 데이터셋 +* YouTube, Google, AIHub, Kaggle에서 안전모 관련 데이터셋 확보 +* Roboflow에서 데이터셋 라벨링 진행 +[Roboflow](https://roboflow.com/) + +# 클래스 +### Detect Model +* 1개의 뚝배기 클래스 + * 0: dduk + +### Classification Model +* 5개의 클래스 + * 0: head + * 1: helmet + * 2: face + * 3: mask + * 4: helmet & mask + +# 프로젝트 코드 (Validation) + +
+ +
+ + +``` planetext + + +``` + +
+
+ + +### 참고[¶]() + +- 지능화캡스톤 과목, 김현용 교수 \ No newline at end of file diff --git a/train/dduk_64_/F1_curve.png b/runs/train/dduk_64_/F1_curve.png similarity index 100% rename from train/dduk_64_/F1_curve.png rename to runs/train/dduk_64_/F1_curve.png diff --git a/train/dduk_64_/PR_curve.png b/runs/train/dduk_64_/PR_curve.png similarity index 100% rename from train/dduk_64_/PR_curve.png rename to runs/train/dduk_64_/PR_curve.png diff --git a/train/dduk_64_/P_curve.png b/runs/train/dduk_64_/P_curve.png similarity index 100% rename from train/dduk_64_/P_curve.png rename to runs/train/dduk_64_/P_curve.png diff --git a/train/dduk_64_/R_curve.png b/runs/train/dduk_64_/R_curve.png similarity index 100% rename from train/dduk_64_/R_curve.png rename to runs/train/dduk_64_/R_curve.png diff --git a/train/dduk_64_/confusion_matrix.png b/runs/train/dduk_64_/confusion_matrix.png similarity index 100% rename from train/dduk_64_/confusion_matrix.png rename to runs/train/dduk_64_/confusion_matrix.png diff --git a/train/dduk_64_/hyp.yaml b/runs/train/dduk_64_/hyp.yaml similarity index 93% rename from train/dduk_64_/hyp.yaml rename to runs/train/dduk_64_/hyp.yaml index 0d2cb01..fa80eb9 100644 --- a/train/dduk_64_/hyp.yaml +++ b/runs/train/dduk_64_/hyp.yaml @@ -1,28 +1,28 @@ -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: 0.05 -cls: 0.5 -cls_pw: 1.0 -obj: 1.0 -obj_pw: 1.0 -iou_t: 0.2 -anchor_t: 4.0 -fl_gamma: 0.0 -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 -mosaic: 1.0 -mixup: 0.0 -copy_paste: 0.0 +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: 0.05 +cls: 0.5 +cls_pw: 1.0 +obj: 1.0 +obj_pw: 1.0 +iou_t: 0.2 +anchor_t: 4.0 +fl_gamma: 0.0 +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 +mosaic: 1.0 +mixup: 0.0 +copy_paste: 0.0 diff --git a/train/dduk_64_/labels.jpg b/runs/train/dduk_64_/labels.jpg similarity index 100% rename from train/dduk_64_/labels.jpg rename to runs/train/dduk_64_/labels.jpg diff --git a/train/dduk_64_/labels_correlogram.jpg b/runs/train/dduk_64_/labels_correlogram.jpg similarity index 100% rename from train/dduk_64_/labels_correlogram.jpg rename to runs/train/dduk_64_/labels_correlogram.jpg diff --git a/train/dduk_64_/opt.yaml b/runs/train/dduk_64_/opt.yaml similarity index 93% rename from train/dduk_64_/opt.yaml rename to runs/train/dduk_64_/opt.yaml index 585472a..e34d754 100644 --- a/train/dduk_64_/opt.yaml +++ b/runs/train/dduk_64_/opt.yaml @@ -1,68 +1,68 @@ -weights: yolov5s.pt -cfg: '' -data: datasets/DDukbaegi2/data.yaml -hyp: - 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: 0.05 - cls: 0.5 - cls_pw: 1.0 - obj: 1.0 - obj_pw: 1.0 - iou_t: 0.2 - anchor_t: 4.0 - fl_gamma: 0.0 - 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 - mosaic: 1.0 - mixup: 0.0 - copy_paste: 0.0 -epochs: 80 -batch_size: 60 -imgsz: 640 -rect: false -resume: false -nosave: false -noval: false -noautoanchor: false -noplots: false -evolve: null -bucket: '' -cache: null -image_weights: false -device: '' -multi_scale: false -single_cls: false -optimizer: SGD -sync_bn: false -workers: 8 -project: runs\train -name: dduk_64_ -exist_ok: false -quad: false -cos_lr: false -label_smoothing: 0.0 -patience: 100 -freeze: -- 0 -save_period: -1 -seed: 0 -local_rank: -1 -entity: null -upload_dataset: false -bbox_interval: -1 -artifact_alias: latest -save_dir: runs\train\dduk_64_ +weights: yolov5s.pt +cfg: '' +data: datasets/DDukbaegi2/data.yaml +hyp: + 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: 0.05 + cls: 0.5 + cls_pw: 1.0 + obj: 1.0 + obj_pw: 1.0 + iou_t: 0.2 + anchor_t: 4.0 + fl_gamma: 0.0 + 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 + mosaic: 1.0 + mixup: 0.0 + copy_paste: 0.0 +epochs: 80 +batch_size: 60 +imgsz: 640 +rect: false +resume: false +nosave: false +noval: false +noautoanchor: false +noplots: false +evolve: null +bucket: '' +cache: null +image_weights: false +device: '' +multi_scale: false +single_cls: false +optimizer: SGD +sync_bn: false +workers: 8 +project: runs\train +name: dduk_64_ +exist_ok: false +quad: false +cos_lr: false +label_smoothing: 0.0 +patience: 100 +freeze: +- 0 +save_period: -1 +seed: 0 +local_rank: -1 +entity: null +upload_dataset: false +bbox_interval: -1 +artifact_alias: latest +save_dir: runs\train\dduk_64_ diff --git a/train/dduk_64_/results.csv b/runs/train/dduk_64_/results.csv similarity index 99% rename from train/dduk_64_/results.csv rename to runs/train/dduk_64_/results.csv index 1421a8d..3aacdf7 100644 --- a/train/dduk_64_/results.csv +++ b/runs/train/dduk_64_/results.csv @@ -1,81 +1,81 @@ - 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, 0.068575, 0.039993, 0, 0.70102, 0.58071, 0.60196, 0.2519, 0.048167, 0.021189, 0, 0.070096, 0.0033226, 0.0033226 - 1, 0.048822, 0.031577, 0, 0.83348, 0.67616, 0.75758, 0.3812, 0.038854, 0.019978, 0, 0.040014, 0.0065736, 0.0065736 - 2, 0.041754, 0.02902, 0, 0.77593, 0.62288, 0.69313, 0.32412, 0.041876, 0.02355, 0, 0.0098492, 0.009742, 0.009742 - 3, 0.037026, 0.02777, 0, 0.83418, 0.71955, 0.80302, 0.42477, 0.035953, 0.01995, 0, 0.0096288, 0.0096288, 0.0096288 - 4, 0.034654, 0.02614, 0, 0.85591, 0.7205, 0.81403, 0.45105, 0.034349, 0.019149, 0, 0.0096288, 0.0096288, 0.0096288 - 5, 0.033087, 0.02533, 0, 0.84811, 0.7377, 0.81351, 0.45187, 0.03501, 0.019692, 0, 0.009505, 0.009505, 0.009505 - 6, 0.031878, 0.024502, 0, 0.84654, 0.76661, 0.83513, 0.46097, 0.035043, 0.018774, 0, 0.0093813, 0.0093813, 0.0093813 - 7, 0.03092, 0.023962, 0, 0.85534, 0.75749, 0.83288, 0.46915, 0.034133, 0.019144, 0, 0.0092575, 0.0092575, 0.0092575 - 8, 0.03049, 0.02335, 0, 0.85638, 0.77501, 0.84568, 0.48421, 0.033064, 0.01893, 0, 0.0091337, 0.0091337, 0.0091337 - 9, 0.029464, 0.022836, 0, 0.87385, 0.75689, 0.83902, 0.47473, 0.033736, 0.019446, 0, 0.00901, 0.00901, 0.00901 - 10, 0.028927, 0.022414, 0, 0.87058, 0.76291, 0.83836, 0.46732, 0.03437, 0.019651, 0, 0.0088863, 0.0088863, 0.0088863 - 11, 0.028566, 0.022261, 0, 0.86504, 0.77011, 0.84318, 0.47604, 0.033465, 0.019213, 0, 0.0087625, 0.0087625, 0.0087625 - 12, 0.027956, 0.021923, 0, 0.85476, 0.77168, 0.84491, 0.48466, 0.032688, 0.01882, 0, 0.0086388, 0.0086388, 0.0086388 - 13, 0.02772, 0.02173, 0, 0.86119, 0.79026, 0.85609, 0.4882, 0.033376, 0.019337, 0, 0.008515, 0.008515, 0.008515 - 14, 0.027131, 0.021128, 0, 0.87567, 0.78199, 0.85549, 0.49365, 0.03306, 0.01928, 0, 0.0083913, 0.0083913, 0.0083913 - 15, 0.026691, 0.021199, 0, 0.87045, 0.78705, 0.85453, 0.48935, 0.032743, 0.019439, 0, 0.0082675, 0.0082675, 0.0082675 - 16, 0.026246, 0.020844, 0, 0.86617, 0.79394, 0.85683, 0.50459, 0.032289, 0.019477, 0, 0.0081437, 0.0081437, 0.0081437 - 17, 0.026001, 0.020515, 0, 0.87474, 0.79456, 0.8614, 0.50697, 0.032548, 0.019612, 0, 0.00802, 0.00802, 0.00802 - 18, 0.025843, 0.020263, 0, 0.87164, 0.78985, 0.85977, 0.49572, 0.03286, 0.019747, 0, 0.0078963, 0.0078963, 0.0078963 - 19, 0.025307, 0.019814, 0, 0.88386, 0.78371, 0.8613, 0.50808, 0.032641, 0.020164, 0, 0.0077725, 0.0077725, 0.0077725 - 20, 0.02506, 0.019861, 0, 0.87474, 0.79407, 0.86474, 0.51026, 0.032239, 0.019819, 0, 0.0076488, 0.0076488, 0.0076488 - 21, 0.024831, 0.019605, 0, 0.88838, 0.79337, 0.86771, 0.52199, 0.032118, 0.020042, 0, 0.007525, 0.007525, 0.007525 - 22, 0.02415, 0.019298, 0, 0.87602, 0.79356, 0.8673, 0.51608, 0.031688, 0.020088, 0, 0.0074013, 0.0074013, 0.0074013 - 23, 0.024106, 0.019282, 0, 0.8797, 0.7958, 0.864, 0.51646, 0.032165, 0.02007, 0, 0.0072775, 0.0072775, 0.0072775 - 24, 0.023864, 0.019081, 0, 0.88117, 0.79456, 0.86429, 0.51661, 0.031982, 0.02004, 0, 0.0071538, 0.0071538, 0.0071538 - 25, 0.023603, 0.018897, 0, 0.88311, 0.80146, 0.8721, 0.52056, 0.031827, 0.019855, 0, 0.00703, 0.00703, 0.00703 - 26, 0.023432, 0.018633, 0, 0.88739, 0.80151, 0.87221, 0.52409, 0.031854, 0.02001, 0, 0.0069063, 0.0069063, 0.0069063 - 27, 0.023217, 0.018547, 0, 0.87712, 0.80711, 0.87094, 0.51917, 0.03161, 0.020015, 0, 0.0067825, 0.0067825, 0.0067825 - 28, 0.022933, 0.018421, 0, 0.8834, 0.80401, 0.87038, 0.52186, 0.031668, 0.020249, 0, 0.0066587, 0.0066587, 0.0066587 - 29, 0.022767, 0.018128, 0, 0.88202, 0.80417, 0.87323, 0.52412, 0.031704, 0.020196, 0, 0.006535, 0.006535, 0.006535 - 30, 0.022603, 0.018222, 0, 0.8803, 0.81024, 0.87504, 0.5244, 0.031576, 0.020058, 0, 0.0064112, 0.0064112, 0.0064112 - 31, 0.022335, 0.01796, 0, 0.88668, 0.80744, 0.87393, 0.52537, 0.03154, 0.020176, 0, 0.0062875, 0.0062875, 0.0062875 - 32, 0.022157, 0.017577, 0, 0.87766, 0.81433, 0.87665, 0.52844, 0.031462, 0.020093, 0, 0.0061637, 0.0061637, 0.0061637 - 33, 0.022158, 0.017984, 0, 0.88273, 0.81092, 0.87597, 0.5282, 0.031602, 0.020117, 0, 0.00604, 0.00604, 0.00604 - 34, 0.021801, 0.017571, 0, 0.88569, 0.81222, 0.87736, 0.5294, 0.031389, 0.020136, 0, 0.0059163, 0.0059163, 0.0059163 - 35, 0.021742, 0.017489, 0, 0.88152, 0.81317, 0.87553, 0.52937, 0.031372, 0.020244, 0, 0.0057925, 0.0057925, 0.0057925 - 36, 0.02136, 0.017304, 0, 0.88046, 0.81354, 0.87724, 0.53145, 0.031391, 0.020415, 0, 0.0056688, 0.0056688, 0.0056688 - 37, 0.02128, 0.017268, 0, 0.88673, 0.80465, 0.87544, 0.53091, 0.031355, 0.020477, 0, 0.005545, 0.005545, 0.005545 - 38, 0.021174, 0.017063, 0, 0.88437, 0.81057, 0.87682, 0.5323, 0.031347, 0.020434, 0, 0.0054212, 0.0054212, 0.0054212 - 39, 0.020998, 0.017043, 0, 0.88227, 0.81226, 0.87718, 0.53318, 0.03129, 0.020569, 0, 0.0052975, 0.0052975, 0.0052975 - 40, 0.020624, 0.016898, 0, 0.88607, 0.8081, 0.87692, 0.53286, 0.031339, 0.020679, 0, 0.0051737, 0.0051737, 0.0051737 - 41, 0.020378, 0.016884, 0, 0.88768, 0.80611, 0.87717, 0.53119, 0.031375, 0.020792, 0, 0.00505, 0.00505, 0.00505 - 42, 0.020381, 0.016592, 0, 0.89306, 0.80343, 0.8783, 0.53234, 0.031363, 0.02084, 0, 0.0049263, 0.0049263, 0.0049263 - 43, 0.020335, 0.016549, 0, 0.88844, 0.80837, 0.87809, 0.53205, 0.031374, 0.020924, 0, 0.0048025, 0.0048025, 0.0048025 - 44, 0.020108, 0.016316, 0, 0.8913, 0.80487, 0.8776, 0.53242, 0.031375, 0.020934, 0, 0.0046788, 0.0046788, 0.0046788 - 45, 0.02003, 0.016276, 0, 0.89132, 0.80413, 0.878, 0.53282, 0.031365, 0.020963, 0, 0.004555, 0.004555, 0.004555 - 46, 0.019874, 0.016299, 0, 0.88557, 0.81015, 0.8783, 0.53268, 0.03137, 0.020986, 0, 0.0044313, 0.0044313, 0.0044313 - 47, 0.01969, 0.016077, 0, 0.88787, 0.8097, 0.87899, 0.53284, 0.03139, 0.021027, 0, 0.0043075, 0.0043075, 0.0043075 - 48, 0.019512, 0.01584, 0, 0.89094, 0.80554, 0.87841, 0.53325, 0.031389, 0.021069, 0, 0.0041837, 0.0041837, 0.0041837 - 49, 0.019293, 0.015728, 0, 0.88709, 0.80849, 0.87744, 0.53346, 0.031429, 0.021154, 0, 0.00406, 0.00406, 0.00406 - 50, 0.019171, 0.015679, 0, 0.88995, 0.80719, 0.87729, 0.53325, 0.031456, 0.021215, 0, 0.0039362, 0.0039362, 0.0039362 - 51, 0.019024, 0.015475, 0, 0.89143, 0.80661, 0.87714, 0.53327, 0.031476, 0.021269, 0, 0.0038125, 0.0038125, 0.0038125 - 52, 0.018813, 0.015559, 0, 0.88925, 0.80781, 0.87713, 0.53341, 0.031494, 0.02133, 0, 0.0036888, 0.0036888, 0.0036888 - 53, 0.018791, 0.01535, 0, 0.88636, 0.80941, 0.87642, 0.53308, 0.031497, 0.021387, 0, 0.003565, 0.003565, 0.003565 - 54, 0.018395, 0.015212, 0, 0.88604, 0.80875, 0.8765, 0.53323, 0.031505, 0.021436, 0, 0.0034413, 0.0034413, 0.0034413 - 55, 0.01827, 0.015173, 0, 0.88587, 0.80929, 0.8763, 0.53306, 0.031523, 0.021478, 0, 0.0033175, 0.0033175, 0.0033175 - 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