Comments (7)
Could you please share the voc_eval.py, so I can check for euclid https://github.com/prabindh/euclid ?
from darknet.
After running ./ darknet detector
on my test set it generates text files for each class in the Pascal VOC format. Check the below example
Image_01389 0.925365 2.702499 139.048599 416.000000 408.688477
Image_01562 0.800577 2.937439 50.000034 144.580612 175.984833
Image_01562 0.007224 17.548409 16.466003 154.005432 340.751160
Image_01562 0.921113 52.459122 28.805679 416.000000 386.246338
Now, I need to use this generated text along with ground truth annotations, to calculate the mAP using
voc_eval.py
Or by using any other standard tool. But for that to happen, the ground truth annotations should be in VOC format. Either I need to convert my annotations to VOC format or create new script to calculate mAP from yolo format
from darknet.
We can also calculate mAP using VOC Devkit
from darknet.
Any idea on this problem
from darknet.
It should be fairly easy to convert the annotation to another format using Python. Given the equation to convert between the two. Do you have the equation handy ?
from darknet.
Yolo
<class> <centerX/imageWidth> <centerY/imageHeight> <bboxWidth/imageWidth> <bboxHeight/imageHeight>
(We'll index this from 0-4)
And for VOC, the format is
Voc
<class> <bboxXMin> <bboxYMin> <bboxXMax> <bboxYMax> (Index this 0-4)
bboxWidth = yolo[3] * imageWidth
bboxHeight = yolo[4] * imageHeight
centerX = yolo[1] * imageWidth
centerY = yolo[2] * imageHeight
voc[1] = centerX - (bboxWidth/2)
voc[2] = centerY - (bboxHeight/2)
voc[3] = centerX + (bboxWidth/2)
voc[4] = centerY + (bboxHeight/2)
Yolo label example
A .xml file is to be created to each text file. I can't upload .xml so I uploaded as a text file. You can ignore the action, pose and difficulty stuff, shown in below example. only name i.e class name and bbox are to be stored
from darknet.
How did you calculate mAP in yolo on your dataset, I asking this out of curiosity, because I have seen many post in Darknet google groups asking how to calculate mAP. And many people doesn't know how to do so. If you have calculated, please share it in the groups
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Related Issues (20)
- Arapaho stream with camera HOT 4
- input.data HOT 2
- Yolo v3 is out, sync with the original code? HOT 3
- 0 prediction with arapaho build (Yolo V3) HOT 2
- upsample_cpu is not defined when GPU=0 HOT 2
- Video of type 8UC1 is not working HOT 9
- After 10 Minutes Arapaho program getting killed HOT 15
- Cuda 9 HOT 6
- darknet-cpp compilation failed on Ubuntu 16.04 HOT 6
- Memory corruption of Arapaho from a library HOT 4
- Cmake compile problem HOT 6
- Differences scores between Darknet and Arapaho HOT 5
- When the width and height of the input picture are not equal, the output box will shift on windows
- Add OpenCV 4.x support HOT 27
- Arapaho build issue HOT 3
- libv4l2: error getting capabilities: Inappropriate ioctl for device HOT 5
- Darknet saved weights are not giving outputs in this HOT 2
- Anyone tested darknet-cpp on Cuda 6.5 (Ubuntu 14.04)? HOT 5
- Trained in two classes the object can't be inference HOT 3
- error "identifier \"ipl_to_image\" is undefined","LineNumber": 234, File: arapaho.cpp HOT 3
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from darknet.