Comments (12)
Thanks for writing the issue.
In the yolov5 folder, when we ran detect.py to a video file, it saves labels folder which includes yolo txt files for all frames of the video.
python3 detect.py --source Pexels\ Videos\ 4800.mp4 --save-txt
-
We will update "Convert video to image frames" feature so that it saves all frames of the video according to the frames per second of the video.
So that every image file exported from RectLabel can correspond to the yolo txt file generated from detect.py. -
We will update "Import YOLO txt files" feature so that it can import yolo txt files generated from detect.py.
Currently the naming rule for each frame is slightly different.
RectLabel: Pexels Videos 4800_frame001.txt
yolov5: Pexels Videos 4800_1.txt
"Convert video to image frames" will be changed to save the first frame as Pexels Videos 4800_001.jpg.
"Import YOLO txt files" will be changed to read Pexels Videos 4800_001.txt, and if not exists, read Pexels Videos 4800_1.txt.
When we could implement this update, we will let you know.
Please let us know your opinon.
from rectlabel-support.
This sounds like a great solution. Thank you!
from rectlabel-support.
The new update version 65 was released.
We improved "Convert video to image frames" to export every frame of the video corresponding to the labels folder generated by detect.py in the yolov5 folder.
When you ran detect.py to a video, the labels folder is generated.
python3 detect.py --source Pexels\ Videos\ 4800.mp4 --save-txt
In the labels folder, there are yolo txt files.
Please use "Convert video to image frames" on RectLabel to the video, choose the second frame suffix option, then you will obtain image frames corresponding to the yolo txt files in the labels folder.
Please let us know your opinion.
from rectlabel-support.
Excellent. I will test it right away!
from rectlabel-support.
OK. So, this mostly works as expected, however, I do have two issues.
-
I have to quit all other programs for the 16,000 images of my detections to be grabbed at 2048 pixels, otherwise it runs out of memory. Smaller dimensions don't cause this issue.
-
The boxes are often on the object of interest, but occasionally they are off or seem to drift -- see attached.
from rectlabel-support.
Thanks for the detailed feedback.
We were testing for short video files.
Using SnapSave, we prepared 2 long video files.
https://snapsave.io/en
Soccer video file
https://www.youtube.com/watch?v=M7yI1V4O2mc
Startup video file
https://www.youtube.com/watch?v=OKD0IAcwMig
Both video files have more than 10000 image frames and the image size is 1920x1080.
For the heap memory problem, we improved our code not to create intermediate files during processing, and for both 2 video files, in our environment, the heap memory during the processing was less than 80MB.
We submitted the new update, when the new update is released, we will let you know.
For the coordinates problem, could you send the image frame and the yolo txt file generated by yolov5 to [email protected]?
from rectlabel-support.
The new update version 66 was released.
We improved the heap memory usage and error processing for "Convert video to image frames".
Please let us know your opinion.
from rectlabel-support.
It still crashes when converting a 2048 x 1080 60 FPS 00:07:11 (~7 minute) ProRes HQ video file.
My computer specs are attached.
from rectlabel-support.
Thanks for the detailed feedback.
We were testing for 30fps videos.
Using iPad, we took 60fps and more than 10 minutes videos.
We could reproduce the application memory problem.
We were retrieving all image frames from the video file at once, so that we divided the processing each by 1000 image frames.
With this update, the processing goes through to the end without encountering the application memory problem.
We submitted the new update to Apple, when the new update is released, we will let you know.
from rectlabel-support.
The new update version 67 was released.
We improved the application memory usage for "Convert video to image frames" when to apply to 60fps more than 10 minutes videos.
Please let us know your feedback.
from rectlabel-support.
Yes, that worked well. Thank you.
from rectlabel-support.
If you have any other requests, please let us know.
from rectlabel-support.
Related Issues (20)
- Unable to open images HOT 9
- RectLabel implemented Segment Anything models to label polygons. HOT 2
- Multiple CoreML application HOT 2
- Image Label / Gallery View HOT 2
- yolov8 text import not working correctly HOT 5
- Exporting Yolo includes 6th column with confidence score I would assume, can we turn this off? HOT 4
- Getting no label file with if ann['iscrowd']: continue statement. HOT 3
- 下载Sam失败 HOT 2
- [Video] can't create images HOT 7
- Current image annotations lost when exporting Create ML JSON HOT 8
- coco2yolo error HOT 1
- crashes on next image/prev image (arrow keys) HOT 3
- Problems with creating polygon with SAM using geo TIF files HOT 2
- Feature Feedback and Launch Inquiry for Windows and Linux systems HOT 1
- Key Error showing up in training HOT 3
- Conversion of annotations from COCO-annotator to yolov8 format HOT 6
- how to save SAM label HOT 3
- keypoints labeling problem HOT 6
- how to show label again after moving files HOT 4
- Create folder error HOT 3
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google ❤️ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from rectlabel-support.