diff --git a/runs/detect/predict49/4.avi b/runs/detect/predict49/4.avi new file mode 100644 index 0000000..e7aed8a Binary files /dev/null and b/runs/detect/predict49/4.avi differ diff --git a/runs/detect/train36/F1_curve.png b/runs/detect/train36/F1_curve.png new file mode 100644 index 0000000..8d55038 Binary files /dev/null and b/runs/detect/train36/F1_curve.png differ diff --git a/runs/detect/train36/PR_curve.png b/runs/detect/train36/PR_curve.png new file mode 100644 index 0000000..9264cae Binary files /dev/null and b/runs/detect/train36/PR_curve.png differ diff --git a/runs/detect/train36/P_curve.png b/runs/detect/train36/P_curve.png new file mode 100644 index 0000000..d7d7558 Binary files /dev/null and b/runs/detect/train36/P_curve.png differ diff --git a/runs/detect/train36/R_curve.png b/runs/detect/train36/R_curve.png new file mode 100644 index 0000000..7dbace1 Binary files /dev/null and b/runs/detect/train36/R_curve.png differ diff --git a/runs/detect/train36/confusion_matrix.png b/runs/detect/train36/confusion_matrix.png new file mode 100644 index 0000000..5a43f5b Binary files /dev/null and b/runs/detect/train36/confusion_matrix.png differ diff --git a/runs/detect/train36/confusion_matrix_normalized.png b/runs/detect/train36/confusion_matrix_normalized.png new file mode 100644 index 0000000..b5ed896 Binary files /dev/null and b/runs/detect/train36/confusion_matrix_normalized.png differ diff --git a/runs/detect/train36/results.csv b/runs/detect/train36/results.csv index dc2a877..c03643d 100644 --- a/runs/detect/train36/results.csv +++ b/runs/detect/train36/results.csv @@ -88,3 +88,14 @@ epoch,time,train/box_loss,train/cls_loss,train/dfl_loss,metrics/precision(B),met 87,602.206,0.44036,0.3477,0.80881,0.97052,0.70044,0.84557,0.62866,1.95032,1.14522,3.08449,0.0002972,0.0002972,0.0002972 88,610.04,0.34605,0.29355,0.82656,0.97052,0.70044,0.84557,0.62866,1.95032,1.14522,3.08449,0.0002774,0.0002774,0.0002774 89,618.104,0.32283,0.27712,0.78311,0.94286,0.70219,0.83861,0.6253,1.94975,1.17272,3.1016,0.0002576,0.0002576,0.0002576 +90,627.396,0.31937,0.2843,0.81442,0.94286,0.70219,0.83861,0.6253,1.94975,1.17272,3.1016,0.0002378,0.0002378,0.0002378 +91,636.531,0.40592,0.3456,0.76639,0.94286,0.70219,0.83861,0.6253,1.94975,1.17272,3.1016,0.000218,0.000218,0.000218 +92,645.424,0.32162,0.25546,0.70747,1,0.70074,0.8321,0.61851,1.94364,1.07547,3.15414,0.0001982,0.0001982,0.0001982 +93,653.162,0.32978,0.27483,0.7712,1,0.70074,0.8321,0.61851,1.94364,1.07547,3.15414,0.0001784,0.0001784,0.0001784 +94,660.746,0.33426,0.27878,0.85918,1,0.70074,0.8321,0.61851,1.94364,1.07547,3.15414,0.0001586,0.0001586,0.0001586 +95,668.458,0.28988,0.27119,0.77331,0.99076,0.68085,0.83074,0.61428,1.94021,0.97339,3.19668,0.0001388,0.0001388,0.0001388 +96,676.066,0.33953,0.28199,0.79338,0.99076,0.68085,0.83074,0.61428,1.94021,0.97339,3.19668,0.000119,0.000119,0.000119 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f'detected_object_{target_class}_{cap.get(cv2.CAP_PROP_POS_FRAMES)}.jpg') cv2.imwrite(save_path, detected_object) - print(f"截图保存至：{save_path}") + print(f"保存：{save_path}") annotated_frame = results[0].plot() cv2.imshow('YOLOv8 Detection', annotated_frame) if cv2.waitKey(1) & 0xFF == ord(' '): diff --git a/src/show.py b/src/show.py new file mode 100644 index 0000000..561f4a0 --- /dev/null +++ b/src/show.py @@ -0,0 +1,42 @@ +import cv2 +from PIL import Image +import os + +folder_path = 'C:/workspace/le-yolo/data/images/train' +for filename in os.listdir(folder_path): + if filename.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp', '.gif')): + img_path = os.path.join(folder_path, filename) + img = cv2.imread(img_path) + height, width, _ = img.shape + + +file_path = 'C:/workspace/le-yolo/data/labels/aut' +txt_files = os.listdir(file_path) +for txt_file in txt_files: + file_path = os.path.join(folder_path, txt_file) + with open(file_path, "r", ) as f: + lines = f.readlines() + for line in lines: + # 解析标注信息 + parts = line.strip().split() + category_id = int(parts[0]) + category_name = 'person' + x_center = float(parts[1]) + y_center = float(parts[2]) + w = float(parts[3]) + h = float(parts[4]) + # 转换为绝对坐标 + x1 = int((x_center - w / 2) * width) + y1 = int((y_center - h / 2) * height) + x2 = int((x_center + w / 2) * width) + y2 = int((y_center + h / 2) * height) + # 在图片上绘制矩形框 + cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 0), 2) + # 在图片上绘制标注类别 + cv2.putText(img, category_name, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (255, 0, 0), 2) + +cv2.imshow('Annotated Image', img) +cv2.waitKey(0) +cv2.destroyAllWindows() + +cv2.imwrite('annotated_image.jpg', img) \ No newline at end of file diff --git a/src/test.py b/src/test.py index 3ca46c7..5638631 100644 --- a/src/test.py +++ b/src/test.py @@ -1,3 +1,3 @@ from ultralytics import YOLO -model = YOLO(r"C:\workspace\le-yolo\runs\detect\train35\weights\best.pt") +model = YOLO(r"C:\workspace\le-yolo\runs\detect\train36\weights\best.pt") results = model.predict("../res/4.mp4", show=True, save=True)