YOLOv3 mAP about map HOT 17 CLOSED

Done! Have a look here.

Basically, all you have to do is add the result.txt to the folder extra/ and run the command python convert_pred_yolo.py

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here is a simple code, works for yolov3 of v4 or any other, adjust the paths, time or even the command for yourself

import os
import subprocess
import time

image_paths_file = '/home/darknet/vadim_configs/test.txt'
path_to_save_images = '/home/darknet/results/'

im_paths = open(image_paths_file, "r").readlines()

obj_dat = "/home/darknet/vadim_configs/obj.data"
yolo_cnf = "/home/darknet/vadim_configs/yolov4-custom.cfg"
yolo_wghts = "/home/darknet/backup/yolov4-custom_best.weights"

for im in im_paths:
    cmd = "./darknet detector test {} {} {} -dont_show \"{}\"".format(obj_dat, yolo_cnf, yolo_wghts, im)

    # The os.setsid() is passed in the argument preexec_fn so
    # it's run after the fork() and before  exec() to run the shell.

    p = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, preexec_fn=os.setsid)

    # it must be adjuste to your inference speed
    # on my rtx2080 takes 6 seconds max
    time.sleep(6)
    # Send the signal to all the process groups
    #os.killpg(os.getpgid(p.pid), signal.SIGTERM)

    image_name = (im.split('/')[-1]).split('.')[0]
    os.rename("predictions.jpg", os.path.join(path_to_save_images, image_name+'.jpg'))
    print("img was saved")

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Done! Have a look here.

Basically, all you have to do is add the result.txt to the folder extra/ and run the command python convert_pred_yolo.py

Hey, i am not able to find the page. could you redirect me please so that i can find the file

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Hey, you can look at my repo:

https://github.com/pratikbhave2/darknet

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I don't get it. What is in your repo?

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I have Modified Yolo to run detector test on multiple images and save each image with bounding boxes, as well as co-ordinates of the bounding box in a text file(separate text file). You can run it with the same command
.
./darknet detector test cfg/voc.data yolo-voc.cfg yolo-voc.weights -dont_show -ext_output < data/train.txt > result.txt

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Hello!

@EscVM I could help you parse that. Do you think you could send me the full file result.txt to here [email protected] ?

Another option, as mentioned by @pratikbhave2, is to modify the files to save the predictions into separate files.

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Thank you @pratikbhave2 and @Cartucho. I'll try both solutions.

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Btw I did the python script with a lot of comments so everything should be easy to understand!

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Thank so much @Cartucho ! I really need to improve my Python skills 🤕

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@Cartucho thanks alot for posts. just a question this is how my result.txt file looks like.

when i execute the script (python convert_pred_yolo.py) , i get this error below

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@buzdarbalooch Hello!
Do you think you could send me a sample of the files? So that I can reproduce the error?

[email protected]

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Done! Have a look here.

Basically, all you have to do is add the result.txt to the folder extra/ and run the command python convert_pred_yolo.py

so how to get result.txt in faster rcnn

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Hey, you can look at my repo:

https://github.com/pratikbhave2/darknet

Hey when i run using your repo in yolov3 i am getting segmentation error.. could you help me out please?

/bin/bash: line 1: 1655 Segmentation fault (core dumped) ./darknet detector test data/obj.data cfg/yolov3_custom_test.cfg /mydrive/weapon_dataset/backup/yolov3_custom_train_last.weights -dont_show -save_labels < data/train.txt > result.txt

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Hey, you can look at my repo:
https://github.com/pratikbhave2/darknet

Hey when i run using your repo in yolov3 i am getting segmentation error.. could you help me out please?

/bin/bash: line 1: 1655 Segmentation fault (core dumped) ./darknet detector test data/obj.data cfg/yolov3_custom_test.cfg /mydrive/weapon_dataset/backup/yolov3_custom_train_last.weights -dont_show -save_labels < data/train.txt > result.txt

I get the same error

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i changed the code from vadimen a little bit, it no need for wait 6s every time, parent process continue after child process exit
and i copy the ground truth to prediction dir too as a comparison
it worked for me

import os
from os import getcwd
import subprocess
import time
import shutil

wd = getcwd()

image_paths_file = "data/train-second/test.txt"
obj_dat = "data/train-second/obj.data"
yolo_cnf = "cfg/yolov4-custom-3.cfg"
yolo_wghts = "backup/yolov4-custom-3_best.weights"
path_to_ground_truth = "data/pic_with_box"

im_paths = open(image_paths_file).read().strip().split('\n')
cfgfilename = yolo_cnf.split('/')[1].split('.')[0]
print(cfgfilename)
path_to_save_predictions = "predictions-%s/"%(cfgfilename)

if not os.path.exists(path_to_save_predictions):
    os.makedirs(path_to_save_predictions)

for im in im_paths:
    if len(im) == 0:
        continue
    cmd = "./darknet detector test %s %s %s -dont_show %s"%(obj_dat, yolo_cnf, yolo_wghts, im)
    print('cmd = %s'%(cmd))
    p = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, preexec_fn=os.setsid)
    # wait max 6s
    p.wait(6)
    # make sure child process exit normally
    if p.poll() != 0:
        print("picture %s predict fails\n"%(im))
        break
    image_name = (im.split('/')[-1]).split('.')[0]
    os.rename("predictions.jpg", os.path.join(path_to_save_predictions, image_name+'.jpg'))
    # cp groud truth near the predictions dir
    # already draw box and saved in path_to_ground_truth dir, if not want to copy, just comment the next line
    shutil.copy(path_to_ground_truth+'/'+image_name+'.jpg', path_to_save_predictions+'/'+image_name+"-truth.jpg")
    print(image_name)

from map.

here is a simple code, works for yolov3 of v4 or any other, adjust the paths, time or even the command for yourself

import os
import subprocess
import time

image_paths_file = '/home/darknet/vadim_configs/test.txt'
path_to_save_images = '/home/darknet/results/'

im_paths = open(image_paths_file, "r").readlines()

obj_dat = "/home/darknet/vadim_configs/obj.data"
yolo_cnf = "/home/darknet/vadim_configs/yolov4-custom.cfg"
yolo_wghts = "/home/darknet/backup/yolov4-custom_best.weights"

for im in im_paths:
    cmd = "./darknet detector test {} {} {} -dont_show \"{}\"".format(obj_dat, yolo_cnf, yolo_wghts, im)

    # The os.setsid() is passed in the argument preexec_fn so
    # it's run after the fork() and before  exec() to run the shell.

    p = subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE, preexec_fn=os.setsid)

    # it must be adjuste to your inference speed
    # on my rtx2080 takes 6 seconds max
    time.sleep(6)
    # Send the signal to all the process groups
    #os.killpg(os.getpgid(p.pid), signal.SIGTERM)

    image_name = (im.split('/')[-1]).split('.')[0]
    os.rename("predictions.jpg", os.path.join(path_to_save_images, image_name+'.jpg'))
    print("img was saved")

Thanks for the code. It works well. How to get output of bounding box coordinates for each image in this file itself?
I'm trying but not possible. Request to assist me.

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