使用YOLOv11进行视频目标检测

使用YOLOv11进行视频目标检测

完整代码

bash 复制代码
import cv2
from ultralytics import YOLO

def predict(chosen_model, img, classes=[], conf=0.5):
    if classes:
        results = chosen_model.predict(img, classes=classes, conf=conf)
    else:
        results = chosen_model.predict(img, conf=conf)

    return results

def predict_and_detect(chosen_model, img, classes=[], conf=0.5, rectangle_thickness=2, text_thickness=1):
    results = predict(chosen_model, img, classes, conf=conf)
    for result in results:
        for box in result.boxes:
            cv2.rectangle(img, (int(box.xyxy[0][0]), int(box.xyxy[0][1])),
                          (int(box.xyxy[0][2]), int(box.xyxy[0][3])), (255, 0, 0), rectangle_thickness)
            cv2.putText(img, f"{result.names[int(box.cls[0])]}",
                        (int(box.xyxy[0][0]), int(box.xyxy[0][1]) - 10),
                        cv2.FONT_HERSHEY_PLAIN, 1, (255, 0, 0), text_thickness)
    return img, results

# defining function for creating a writer (for mp4 videos)
def create_video_writer(video_cap, output_filename):
    # grab the width, height, and fps of the frames in the video stream.
    frame_width = int(video_cap.get(cv2.CAP_PROP_FRAME_WIDTH))
    frame_height = int(video_cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
    fps = int(video_cap.get(cv2.CAP_PROP_FPS))
    # initialize the FourCC and a video writer object
    fourcc = cv2.VideoWriter_fourcc(*'MP4V')
    writer = cv2.VideoWriter(output_filename, fourcc, fps,
                             (frame_width, frame_height))
    return writer

model = YOLO("yolo11x.pt")

output_filename = "YourFilename.mp4"

video_path = r"YourVideoPath.mp4"
cap = cv2.VideoCapture(video_path)
writer = create_video_writer(cap, output_filename)
while True:
    success, img = cap.read()
    if not success:
        break
    result_img, _ = predict_and_detect(model, img, classes=[], conf=0.5)
    writer.write(result_img)
    cv2.imshow("Image", result_img)
    
    cv2.waitKey(1)
writer.release()

参考资料:

1.https://blog.csdn.net/qq_42589613/article/details/142729428

2.https://blog.csdn.net/java1314777/article/details/142665078

相关推荐
weixin_446260851 小时前
AVA-Encoder:面向智能体原生视频表征学习框架
学习·音视频
cdprinter1 小时前
信刻——留置谈话音视频数据集中自动刻录归档解决方案
自动化·音视频
美狐美颜sdk3 小时前
直播APP开发技术架构解析:从音视频流到第三方美颜SDK接入的完整方案
大数据·人工智能·音视频·美颜sdk·美颜api
阿童木写作5 小时前
跨境电商图片翻译工具推荐:跨马翻译批量处理视频字幕与抠图
python·音视频
奈斯先生Vector5 小时前
AI 视频不是会动的图片:用 Shot Contract、时间码与音画质检构建可交付流水线
人工智能·重构·架构·prompt·aigc·音视频
ai产品老杨5 小时前
AI视频分析并发优化参数配置说明
人工智能·音视频
怪奇云呼军5 小时前
G.711、Opus 和重采样会拖慢识别吗?闪电智能VoiceAgent 的音频入口怎么选
java·人工智能·python·算法·云计算·音视频
DogDaoDao6 小时前
MSU 2026 视频编解码大赛放榜深度解读
音视频·视频编解码·hevc·av1·h266·msu·avs
caimouse7 小时前
ReactOS 图形系统分析(2):视频端口驱动 videoprt.sys
音视频
AI视觉网奇8 小时前
动作识别 视频理解大模型
开发语言·python·音视频