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ultralytics / yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
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How to display real-time MP4 processing results #11485

Open hnulmz3 opened 1 year ago

hnulmz3 commented 1 year ago

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Question

Using decect.py to test MP4 video has only one result output and an intermediate 'Video 1/1 (469/486).......... 640x384 (no detections), text display of 80.6ms', what should I do if I want to display the video in real time?

Additional

Sorry, I'm a green hand

github-actions[bot] commented 1 year ago

👋 Hello @hnulmz3, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.

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hnulmz3 commented 1 year ago

谢谢，已收到

hnulmz3 commented 1 year ago

OK，i got it by myself

glenn-jocher commented 1 year ago

@hnulmz3 that's great to hear! Don't hesitate to reach out if you have any further questions or if there's anything we can assist you with in the future. Have a great day!

github-actions[bot] commented 1 year ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 1 year ago

谢谢，已收到

glenn-jocher commented 1 year ago

@hnulmz3 太好了，很高兴您已经解决了问题！如果将来还有任何问题或需要我们的帮助，请随时告诉我们。祝您拥有愉快的一天！

github-actions[bot] commented 1 year ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 1 year ago

谢谢，已收到

glenn-jocher commented 1 year ago

@hnulmz3 感谢您的反馈！如果将来还有任何问题或需要我们的帮助，请随时告诉我们。祝您拥有愉快的一天！

github-actions[bot] commented 1 year ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 1 year ago

谢谢，已收到

glenn-jocher commented 1 year ago

@hnulmz3 you're welcome! If you have any other questions or need further assistance, feel free to ask.

github-actions[bot] commented 1 year ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 1 year ago

谢谢，已收到

glenn-jocher commented 1 year ago

@hnulmz3 您好！非常感谢您的反馈！如果您有任何其他问题或需要进一步的帮助，请随时告知我们。祝您使用 YOLOv5 的愉快！

github-actions[bot] commented 12 months ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 12 months ago

谢谢，已收到

glenn-jocher commented 12 months ago

@hnulmz3 你好！

感谢你的反馈！如果你还有其他问题或需要进一步的帮助，请随时告诉我们。我们团队一直致力于提供高质量的支持和解决方案。祝你使用 YOLOv5 愉快！

最好的祝愿！

github-actions[bot] commented 10 months ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 10 months ago

谢谢，已收到

glenn-jocher commented 10 months ago

@hnulmz3 great to hear that you've received the response. If you have any further questions or need additional assistance, please feel free to ask. We're here to help!

github-actions[bot] commented 9 months ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 9 months ago

谢谢，已收到

glenn-jocher commented 9 months ago

@hnulmz3 欢迎！如果您有任何其他问题，请随时提出。祝您使用 YOLOv5 愉快！

github-actions[bot] commented 8 months ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 8 months ago

谢谢，已收到

glenn-jocher commented 8 months ago

@hnulmz3 不客气！如果将来需要帮助，随时欢迎回来。祝您一切顺利！ 😊👍

github-actions[bot] commented 7 months ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 7 months ago

谢谢，已收到

glenn-jocher commented 7 months ago

@hnulmz3 很好！如果您有其他问题或需要进一步的帮助，请随时告知。祝您使用YOLOv5愉快！🌟

github-actions[bot] commented 6 months ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 6 months ago

谢谢，已收到

glenn-jocher commented 6 months ago

@hnulmz3 you're welcome! If you have more questions or need further assistance in the future, feel free to reach out. Happy coding with YOLOv5! 😊🚀

github-actions[bot] commented 5 months ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 5 months ago

谢谢，已收到

glenn-jocher commented 5 months ago

You're welcome! If you have any more questions or need assistance, just let us know. Happy to help! 😊

github-actions[bot] commented 4 months ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 4 months ago

谢谢，已收到

glenn-jocher commented 4 months ago

You're welcome! If there's anything else you need help with, just let me know. Happy coding! 😊

github-actions[bot] commented 3 months ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 3 months ago

谢谢，已收到

glenn-jocher commented 3 months ago

Hello @hnulmz3,

Thank you for reaching out! If you want to display real-time processing results while testing an MP4 video using detect.py, you can modify the script to show the video frames with detections as they are processed.

Here's a step-by-step guide to help you achieve this:

  1. Ensure you have the latest version: Make sure you are using the most recent versions of torch and YOLOv5. You can update YOLOv5 by running:

    git pull
pip install -U -r requirements.txt

  2. Modify detect.py: You can add code to display each frame with OpenCV. Below is an example modification to detect.py:

    import cv2
from pathlib import Path
import torch
from models.common import DetectMultiBackend
from utils.datasets import LoadStreams, LoadImages
from utils.general import check_img_size, non_max_suppression, scale_coords, xyxy2xywh, strip_optimizer, set_logging, increment_path
from utils.plots import plot_one_box
from utils.torch_utils import select_device, load_classifier, time_synchronized

# Initialize
set_logging()
device = select_device('')
half = device.type != 'cpu'  # half precision only supported on CUDA

# Load model
model = DetectMultiBackend(weights, device=device, dnn=dnn)
stride, names, pt = model.stride, model.names, model.pt
imgsz = check_img_size(imgsz, s=stride)  # check image size

# Dataloader
dataset = LoadImages(source, img_size=imgsz, stride=stride, auto=pt)
bs = 1  # batch_size

# Run inference
model.warmup(imgsz=(1 if pt else bs, 3, *imgsz))  # warmup
seen, dt = 0, [0.0, 0.0, 0.0]
for path, img, im0s, vid_cap in dataset:
    img = torch.from_numpy(img).to(device)
    img = img.half() if half else img.float()  # uint8 to fp16/32
    img /= 255.0  # 0 - 255 to 0.0 - 1.0
    if img.ndimension() == 3:
        img = img.unsqueeze(0)

    # Inference
    t1 = time_synchronized()
    pred = model(img, augment=augment, visualize=visualize)
    t2 = time_synchronized()

    # NMS
    pred = non_max_suppression(pred, conf_thres, iou_thres, classes, agnostic_nms)
    t3 = time_synchronized()

    # Process detections
    for i, det in enumerate(pred):  # detections per image
        seen += 1
        p, s, im0, frame = path, '', im0s.copy(), getattr(dataset, 'frame', 0)

        p = Path(p)  # to Path
        save_path = str(save_dir / p.name)  # img.jpg
        txt_path = str(save_dir / 'labels' / p.stem) + ('' if dataset.mode == 'image' else f'_{frame}')  # img.txt
        s += '%gx%g ' % img.shape[2:]  # print string
        gn = torch.tensor(im0.shape)[[1, 0, 1, 0]]  # normalization gain whwh
        imc = im0.copy() if save_crop else im0  # for save_crop
        annotator = Annotator(im0, line_width=line_thickness, example=str(names))
        if len(det):
            # Rescale boxes from img_size to im0 size
            det[:, :4] = scale_coords(img.shape[2:], det[:, :4], im0.shape).round()

            # Print results
            for c in det[:, -1].unique():
                n = (det[:, -1] == c).sum()  # detections per class
                s += f"{n} {names[int(c)]}{'s' * (n > 1)}, "  # add to string

            # Write results
            for *xyxy, conf, cls in reversed(det):
                if save_txt:  # Write to file
                    xywh = (xyxy2xywh(torch.tensor(xyxy).view(1, 4)) / gn).view(-1).tolist()  # normalized xywh
                    line = (cls, *xywh, conf) if save_conf else (cls, *xywh)  # label format
                    with open(txt_path + '.txt', 'a') as f:
                        f.write(('%g ' * len(line)).rstrip() % line + '\n')

                if save_img or view_img:  # Add bbox to image
                    label = f'{names[int(cls)]} {conf:.2f}'
                    plot_one_box(xyxy, im0, label=label, color=colors[int(cls)], line_thickness=line_thickness)

        # Stream results
        if view_img:
            cv2.imshow(str(p), im0)
            if cv2.waitKey(1) == ord('q'):  # q to quit
                raise StopIteration

        # Save results (image with detections)
        if save_img:
            if dataset.mode == 'image':
                cv2.imwrite(save_path, im0)
            else:  # 'video' or 'stream'
                if vid_path != save_path:  # new video
                    vid_path = save_path
                    if isinstance(vid_writer, cv2.VideoWriter):
                        vid_writer.release()  # release previous video writer
                    if vid_cap:  # video
                        fps = vid_cap.get(cv2.CAP_PROP_FPS)
                        w = int(vid_cap.get(cv2.CAP_PROP_FRAME_WIDTH))
                        h = int(vid_cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
                    else:  # stream
                        fps, w, h = 30, im0.shape[1], im0.shape[0]
                    save_path = str(Path(save_path).with_suffix('.mp4'))  # force *.mp4 suffix on results videos
                    vid_writer = cv2.VideoWriter(save_path, cv2.VideoWriter_fourcc(*'mp4v'), fps, (w, h))
                vid_writer.write(im0)

if save_txt or save_img:
    s = f"\n{len(list(save_dir.glob('labels/*.txt')))} labels saved to {save_dir / 'labels'}" if save_txt else ''
    print(f"Results saved to {save_dir}{s}")
print(f'Done. ({t3 - t0:.3f}s)')

  3. Run the modified script: Execute the modified detect.py script with your video file as the source:

    python detect.py --source path/to/your/video.mp4 --view-img

This modification will display the video frames with detections in real-time. If you encounter any issues or have further questions, feel free to ask!

github-actions[bot] commented 2 months ago

👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.

For additional resources and information, please see the links below:

Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!

Thank you for your contributions to YOLO 🚀 and Vision AI ⭐

hnulmz3 commented 2 months ago

谢谢，已收到

glenn-jocher commented 2 months ago

Hello @hnulmz3,

Thank you for your message! If you have any further questions or need additional assistance with YOLOv5, please feel free to ask. We're here to help you get the most out of the YOLOv5 repository.

If you were referring to displaying real-time MP4 processing results, please ensure you have followed the steps provided earlier. If you encounter any issues, make sure you are using the latest version of YOLOv5 by running:

git pull
pip install -U -r requirements.txt

If the issue persists, please provide more details about the problem, and we will do our best to assist you further.

Happy coding! 😊