Merge pull request #80 from NUTFes/feat/nose/72-bring-number-class

学習結果を追加
NUTFes · Sep 8, 2024 · b31c4b6 · b31c4b6
2 parents 51a1fdf + d9d8699
commit b31c4b6
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Showing 109 changed files with 516 additions and 28 deletions.
diff --git a/.gitattributes b/.gitattributes
@@ -1,3 +1,11 @@
 *.pt filter=lfs diff=lfs merge=lfs -text
 yolo_fine_tuning/runs/detect/train14/weights/last.pt filter=lfs diff=lfs merge=lfs -text
 yolo_fine_tuning/runs/detect/train14/weights/best.pt filter=lfs diff=lfs merge=lfs -text
+yolo_fine_tuning/runs/detect/m_640_FHD/weights/last.pt filter=lfs diff=lfs merge=lfs -text
+yolo_fine_tuning/runs/detect/m_640_FHD/weights/best.pt filter=lfs diff=lfs merge=lfs -text
+yolo_fine_tuning/runs/detect/m_FHD_rect/weights/last.pt filter=lfs diff=lfs merge=lfs -text
+yolo_fine_tuning/runs/detect/m_FHD_rect/weights/best.pt filter=lfs diff=lfs merge=lfs -text
+yolo_fine_tuning/runs/detect/l_640_FHD/weights/last.pt filter=lfs diff=lfs merge=lfs -text
+yolo_fine_tuning/runs/detect/l_640_FHD/weights/best.pt filter=lfs diff=lfs merge=lfs -text
+yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/weights/last.pt filter=lfs diff=lfs merge=lfs -text
+yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/weights/best.pt filter=lfs diff=lfs merge=lfs -text
diff --git a/.gitignore b/.gitignore
@@ -9,3 +9,4 @@ __pycache__/
 /sahi
 .env
 raspi/result/prediction_visual.png
+*.pt
diff --git a/raspi/number/main.py b/raspi/number/main.py
@@ -8,11 +8,11 @@
 load_dotenv()
 
 # パスの設定
-HOME_DIR = os.environ["HOME"]
-PATH = HOME_DIR + "/yolo_fine_tuning/runs/detect/train14/weights/best.pt"
+HOME_DIR = os.environ["HOME_DIR"]
+PATH = HOME_DIR + "/yolo_fine_tuning/runs/detect/l_640_FHD/weights/best.pt"
 
 # YOLOモデルのロード
-model = YOLO(PATH)
+model = YOLO(PATH, verbose=False)
 
 # カメラデバイスを開く
 cap = cv2.VideoCapture(0)
@@ -25,27 +25,34 @@
 while cap.isOpened():
     # リアルタイム画像からフレームを読み込む
     ret, frame = cap.read()
+
 
     # フレームが確認できる：true
     if ret:
         # フレームごとに物体検知を行う
-        results = model.track(frame)
+        gray_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        gray_frame_rgb = cv2.cvtColor(gray_frame, cv2.COLOR_GRAY2RGB)
 
+        results = model.track(gray_frame_rgb, device='cuda')
+        # results = model.track(frame, imgsz=(1920, 1080), device='cuda')
+
+
         # 検知結果を描画
         annotated_frame = results[0].plot()
 
+        # show
+        cv2.imshow("Frame",annotated_frame) 
+
         # 出力動画にフレームを書き込む
         out.write(annotated_frame)
 
-        # フレームを表示
-        cv2.imshow("Frame", annotated_frame)
-
         # 'q'キーが押されたら終了
         if cv2.waitKey(1) & 0xFF == ord("q"):
             break
     else:
         break
 
+
 # リソースの解放
 cap.release()
 out.release()

diff --git a/raspi/number/model.md b/raspi/number/model.md
@@ -0,0 +1,17 @@
+- m_640_FHD
+  - グレースケールにしたFHDの画像を学習させたもの
+  - 今のところ一番使い勝手が良い
+  - 背景画像が複数種類
+- m_FHD_rect
+  - グレースケールにし、画像サイズが普遍になるように設定し学習させたもの
+  - 微妙な精度
+  - 背景を統一
+- l_640_FHD
+  - model8l.ptに追加学習したもの
+  - オプション内容はm_640_FHDと同じ
+  - 重くて使いづらい
+  - 白以外のナンバーの精度がとても悪い
+  - 背景を統一
+
+
+
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_1.jpg b/yolo_fine_tuning/resorces/dataset/background/background_1.jpg
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_1.png b/yolo_fine_tuning/resorces/dataset/background/background_1.png
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_2.jpg b/yolo_fine_tuning/resorces/dataset/background/background_2.jpg
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_2.png b/yolo_fine_tuning/resorces/dataset/background/background_2.png
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_3.jpg b/yolo_fine_tuning/resorces/dataset/background/background_3.jpg
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_3.png b/yolo_fine_tuning/resorces/dataset/background/background_3.png
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_4.jpg b/yolo_fine_tuning/resorces/dataset/background/background_4.jpg
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_4.png b/yolo_fine_tuning/resorces/dataset/background/background_4.png
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_5.jpg b/yolo_fine_tuning/resorces/dataset/background/background_5.jpg
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_5.png b/yolo_fine_tuning/resorces/dataset/background/background_5.png
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_6.jpg b/yolo_fine_tuning/resorces/dataset/background/background_6.jpg
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_6.png b/yolo_fine_tuning/resorces/dataset/background/background_6.png
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_7.jpg b/yolo_fine_tuning/resorces/dataset/background/background_7.jpg
diff --git a/yolo_fine_tuning/resorces/dataset/background/background_7.png b/yolo_fine_tuning/resorces/dataset/background/background_7.png
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/F1_curve.png b/yolo_fine_tuning/runs/detect/l_640_FHD/F1_curve.png
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/PR_curve.png b/yolo_fine_tuning/runs/detect/l_640_FHD/PR_curve.png
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/P_curve.png b/yolo_fine_tuning/runs/detect/l_640_FHD/P_curve.png
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/R_curve.png b/yolo_fine_tuning/runs/detect/l_640_FHD/R_curve.png
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/confusion_matrix.png b/yolo_fine_tuning/runs/detect/l_640_FHD/confusion_matrix.png
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/confusion_matrix_normalized.png b/yolo_fine_tuning/runs/detect/l_640_FHD/confusion_matrix_normalized.png
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/labels.jpg b/yolo_fine_tuning/runs/detect/l_640_FHD/labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/labels_correlogram.jpg b/yolo_fine_tuning/runs/detect/l_640_FHD/labels_correlogram.jpg
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/results.csv b/yolo_fine_tuning/runs/detect/l_640_FHD/results.csv
@@ -0,0 +1,6 @@
+                  epoch,         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,                0.67685,                 0.3953,                 0.8331,                0.98654,                0.88973,                0.93778,                0.74885,                0.63685,                0.33004,                0.79577,             0.00066644,             0.00066644,             0.00066644
+                      2,                0.50683,                0.29285,                0.80155,                0.99366,                0.89526,                0.94802,                0.78474,                0.52749,                0.28119,                0.78093,              0.0010692,              0.0010692,              0.0010692
+                      3,                0.42866,                0.25384,                0.79112,                0.99529,                0.91066,                0.95817,                0.82919,                0.40829,                0.23185,                0.77232,              0.0012079,              0.0012079,              0.0012079
+                      4,                 0.3716,                0.22142,                0.78428,                0.98165,                0.92475,                0.96069,                 0.8543,                0.36759,                0.20497,                0.76868,               0.000812,               0.000812,               0.000812
+                      5,                0.32738,                0.19429,                0.77937,                 0.9889,                0.92465,                0.96251,                0.86915,                0.34049,                0.19252,                0.76625,               0.000416,               0.000416,               0.000416
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/results.png b/yolo_fine_tuning/runs/detect/l_640_FHD/results.png
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/train_batch0.jpg b/yolo_fine_tuning/runs/detect/l_640_FHD/train_batch0.jpg
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/train_batch1.jpg b/yolo_fine_tuning/runs/detect/l_640_FHD/train_batch1.jpg
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/train_batch2.jpg b/yolo_fine_tuning/runs/detect/l_640_FHD/train_batch2.jpg
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/val_batch0_labels.jpg b/yolo_fine_tuning/runs/detect/l_640_FHD/val_batch0_labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/val_batch0_pred.jpg b/yolo_fine_tuning/runs/detect/l_640_FHD/val_batch0_pred.jpg
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/val_batch1_labels.jpg b/yolo_fine_tuning/runs/detect/l_640_FHD/val_batch1_labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/val_batch1_pred.jpg b/yolo_fine_tuning/runs/detect/l_640_FHD/val_batch1_pred.jpg
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/val_batch2_labels.jpg b/yolo_fine_tuning/runs/detect/l_640_FHD/val_batch2_labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/val_batch2_pred.jpg b/yolo_fine_tuning/runs/detect/l_640_FHD/val_batch2_pred.jpg
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/weights/.gitignore b/yolo_fine_tuning/runs/detect/l_640_FHD/weights/.gitignore
@@ -0,0 +1 @@
+!*.pt
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/weights/best.pt b/yolo_fine_tuning/runs/detect/l_640_FHD/weights/best.pt
diff --git a/yolo_fine_tuning/runs/detect/l_640_FHD/weights/last.pt b/yolo_fine_tuning/runs/detect/l_640_FHD/weights/last.pt
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/F1_curve.png b/yolo_fine_tuning/runs/detect/m_640_FHD/F1_curve.png
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/PR_curve.png b/yolo_fine_tuning/runs/detect/m_640_FHD/PR_curve.png
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/P_curve.png b/yolo_fine_tuning/runs/detect/m_640_FHD/P_curve.png
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/R_curve.png b/yolo_fine_tuning/runs/detect/m_640_FHD/R_curve.png
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/confusion_matrix.png b/yolo_fine_tuning/runs/detect/m_640_FHD/confusion_matrix.png
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/confusion_matrix_normalized.png b/yolo_fine_tuning/runs/detect/m_640_FHD/confusion_matrix_normalized.png
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/labels.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD/labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/labels_correlogram.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD/labels_correlogram.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/results.csv b/yolo_fine_tuning/runs/detect/m_640_FHD/results.csv
@@ -0,0 +1,6 @@
+                  epoch,         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,                0.70887,                0.41523,                0.83844,                0.98408,                0.87413,                0.93341,                0.74358,                 0.6663,                0.34132,                0.80185,             0.00066644,             0.00066644,             0.00066644
+                      2,                0.53583,                0.30824,                0.80444,                0.98859,                0.90243,                0.95113,                0.80468,                0.49235,                0.27633,                0.78274,              0.0010692,              0.0010692,              0.0010692
+                      3,                0.45435,                0.26698,                0.79379,                0.98149,                0.91482,                 0.9538,                0.83099,                0.42844,                0.25081,                0.77453,              0.0012079,              0.0012079,              0.0012079
+                      4,                0.39643,                0.23437,                0.78659,                0.99131,                0.91356,                 0.9576,                0.83999,                0.43174,                0.23201,                0.77332,               0.000812,               0.000812,               0.000812
+                      5,                 0.3511,                0.20764,                 0.7817,                0.99418,                0.91299,                0.95326,                0.84083,                 0.4017,                0.21327,                0.77038,               0.000416,               0.000416,               0.000416
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/results.png b/yolo_fine_tuning/runs/detect/m_640_FHD/results.png
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/train_batch0.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD/train_batch0.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/train_batch1.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD/train_batch1.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/train_batch2.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD/train_batch2.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/val_batch0_labels.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD/val_batch0_labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/val_batch0_pred.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD/val_batch0_pred.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/val_batch1_labels.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD/val_batch1_labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/val_batch1_pred.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD/val_batch1_pred.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/val_batch2_labels.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD/val_batch2_labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/val_batch2_pred.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD/val_batch2_pred.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/weights/.gitignore b/yolo_fine_tuning/runs/detect/m_640_FHD/weights/.gitignore
@@ -0,0 +1 @@
+!*.pt
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/weights/best.pt b/yolo_fine_tuning/runs/detect/m_640_FHD/weights/best.pt
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD/weights/last.pt b/yolo_fine_tuning/runs/detect/m_640_FHD/weights/last.pt
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/F1_curve.png b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/F1_curve.png
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/PR_curve.png b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/PR_curve.png
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/P_curve.png b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/P_curve.png
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/R_curve.png b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/R_curve.png
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/confusion_matrix.png b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/confusion_matrix.png
diff --git a/...fine_tuning/runs/detect/m_640_FHD_color_BackOne/confusion_matrix_normalized.png b/...fine_tuning/runs/detect/m_640_FHD_color_BackOne/confusion_matrix_normalized.png
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/labels.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/labels_correlogram.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/labels_correlogram.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/results.csv b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/results.csv
@@ -0,0 +1,6 @@
+                  epoch,         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,                0.58449,                0.34396,                0.81602,                0.98443,                0.93586,                0.97909,                0.81684,                0.55458,                0.29184,                0.78206,             0.00066644,             0.00066644,             0.00066644
+                      2,                0.42472,                0.24457,                0.78931,                 0.9742,                0.95333,                0.98473,                0.86903,                0.44232,                0.25442,                0.77217,              0.0010692,              0.0010692,              0.0010692
+                      3,                0.36312,                0.21305,                0.78243,                0.98055,                0.93847,                0.98212,                0.90056,                0.34956,                0.21314,                0.76746,              0.0012079,              0.0012079,              0.0012079
+                      4,                0.32035,                0.18845,                0.77774,                0.98702,                0.94725,                0.98425,                0.89835,                0.36013,                0.20169,                0.76503,               0.000812,               0.000812,               0.000812
+                      5,                0.27901,                0.16451,                0.77428,                0.98724,                 0.9509,                0.98448,                0.92356,                0.28607,                0.16842,                0.76276,               0.000416,               0.000416,               0.000416
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/results.png b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/results.png
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/train_batch0.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/train_batch0.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/train_batch1.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/train_batch1.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/train_batch2.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/train_batch2.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/val_batch0_labels.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/val_batch0_labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/val_batch0_pred.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/val_batch0_pred.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/val_batch1_labels.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/val_batch1_labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/val_batch1_pred.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/val_batch1_pred.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/val_batch2_labels.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/val_batch2_labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/val_batch2_pred.jpg b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/val_batch2_pred.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/weights/.gitignore b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/weights/.gitignore
@@ -0,0 +1 @@
+!*.pt
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/weights/best.pt b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/weights/best.pt
diff --git a/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/weights/last.pt b/yolo_fine_tuning/runs/detect/m_640_FHD_color_BackOne/weights/last.pt
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/F1_curve.png b/yolo_fine_tuning/runs/detect/m_FHD_rect/F1_curve.png
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/PR_curve.png b/yolo_fine_tuning/runs/detect/m_FHD_rect/PR_curve.png
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/P_curve.png b/yolo_fine_tuning/runs/detect/m_FHD_rect/P_curve.png
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/R_curve.png b/yolo_fine_tuning/runs/detect/m_FHD_rect/R_curve.png
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/confusion_matrix.png b/yolo_fine_tuning/runs/detect/m_FHD_rect/confusion_matrix.png
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/confusion_matrix_normalized.png b/yolo_fine_tuning/runs/detect/m_FHD_rect/confusion_matrix_normalized.png
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/labels.jpg b/yolo_fine_tuning/runs/detect/m_FHD_rect/labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/labels_correlogram.jpg b/yolo_fine_tuning/runs/detect/m_FHD_rect/labels_correlogram.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/results.csv b/yolo_fine_tuning/runs/detect/m_FHD_rect/results.csv
@@ -0,0 +1,6 @@
+                  epoch,         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,                0.57716,                0.37898,                0.89307,                0.99394,                0.98269,                0.99459,                0.84107,                 0.6096,                0.33031,                0.82871,             0.00066644,             0.00066644,             0.00066644
+                      2,                0.43363,                 0.2752,                0.83879,                0.99862,                0.99048,                0.99499,                0.91155,                0.40265,                0.25293,                0.78532,              0.0010692,              0.0010692,              0.0010692
+                      3,                  0.364,                0.23379,                0.81604,                0.99875,                0.99116,                0.99499,                0.93123,                0.34977,                0.22145,                0.77599,              0.0012079,              0.0012079,              0.0012079
+                      4,                0.31465,                0.20109,                0.80336,                0.99934,                0.99488,                0.99499,                0.95489,                 0.2688,                0.19069,                0.76717,               0.000812,               0.000812,               0.000812
+                      5,                0.26596,                0.16881,                0.79202,                0.99945,                0.99668,                  0.995,                0.97108,                0.22011,                0.15982,                0.75971,               0.000416,               0.000416,               0.000416
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/results.png b/yolo_fine_tuning/runs/detect/m_FHD_rect/results.png
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/train_batch0.jpg b/yolo_fine_tuning/runs/detect/m_FHD_rect/train_batch0.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/train_batch1.jpg b/yolo_fine_tuning/runs/detect/m_FHD_rect/train_batch1.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/train_batch2.jpg b/yolo_fine_tuning/runs/detect/m_FHD_rect/train_batch2.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/val_batch0_labels.jpg b/yolo_fine_tuning/runs/detect/m_FHD_rect/val_batch0_labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/val_batch0_pred.jpg b/yolo_fine_tuning/runs/detect/m_FHD_rect/val_batch0_pred.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/val_batch1_labels.jpg b/yolo_fine_tuning/runs/detect/m_FHD_rect/val_batch1_labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/val_batch1_pred.jpg b/yolo_fine_tuning/runs/detect/m_FHD_rect/val_batch1_pred.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/val_batch2_labels.jpg b/yolo_fine_tuning/runs/detect/m_FHD_rect/val_batch2_labels.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/val_batch2_pred.jpg b/yolo_fine_tuning/runs/detect/m_FHD_rect/val_batch2_pred.jpg
diff --git a/yolo_fine_tuning/runs/detect/m_FHD_rect/weights/.gitignore b/yolo_fine_tuning/runs/detect/m_FHD_rect/weights/.gitignore
@@ -0,0 +1 @@
+!*.pt
diff --git a/yolo_fine_tuning/src/convert_ground_truth_to_yolo.py b/yolo_fine_tuning/src/convert_ground_truth_to_yolo.py
@@ -10,7 +10,7 @@
 # 定義
 inputPath = HOME_DIR + "/yolo_fine_tuning/resorces/dataset/output_ground_truth"
 # outputPath = "./dataset/yolo"
-outputPath = "./yolo"
+outputPath = HOME_DIR + "/yolo_fine_tuning/yolo"
 manifest = "output.manifest"
 # 学習用と検証用の分割比率
 ratio = 0.8  # 8対2に分割する
-Original file line number
+Diff line change
@@ Expand Up / @@ -9,3 +9,4 @@ __pycache__/ @@
     /sahi
     .env
     raspi/result/prediction_visual.png
+    *.pt