Loss graph during training

[abeyang00]

Is there a way to show loss graph during training like tensorflow?

[springkim]

Hi @abeyang00 Here! https://github.com/AlexeyAB/darknet. He made loss plot for training.

[abeyang00]

@springkim can you tell me where the plot is located in his folder? is it in .c file in src??

[ahsan856jalal]

https://github.com/AlexeyAB/darknet/issues/504#issuecomment-377500006 your answer is at the bottom

[Caroline1994]

can someone tell me how to show loss graph during training when i use pjreddie's darknet

[Sikandarkhan]

Any update on this thread?

[rbarman]

I found one solution here : https://github.com/Jumabek/darknet_scripts/#how-to-plot-yolo-loss

You basically need to save the output of ./darknet detector train <> into a log file and then python plot_yolo_log.py log_file.log

Note that the plot does not show in a jupyter-notebook even with %matplotlib inline. A work around is to copy all plot related code from https://github.com/Jumabek/darknet_scripts/blob/master/plot_yolo_log.py into a new function.

[AlexeyAB]

You can use repo https://github.com/AlexeyAB/darknet that shows Loss & mAP chart during Training:

[groszste]

@AlexeyAB is this plot of the training loss or validation loss? If training loss, do you have a way of viewing the validation loss?

[AlexeyAB]

@groszste It is Training loss and Validation mAP. For me it isn't necessary to see Validation loss, it is much better to see Validation mAP.

[JakupGuven]

@AlexeyAB What commands do you use to display validation mAP during training?

[kschwethelm]

@JakupGuven

From README: https://github.com/AlexeyAB/darknet/blob/master/README.md

"Or just train with -map flag:

darknet.exe detector train data/obj.data yolo-obj.cfg darknet53.conv.74 -map

So you will see mAP-chart (red-line) in the Loss-chart Window. mAP will be calculated for each 4 Epochs using valid=valid.txt file that is specified in obj.data file (1 Epoch = images_in_train_txt / batch iterations)"

[yjdeveloper]

I have followed the steps given by Mr. @AlexeyAB and got the red line but my problem is how to plot a mAP after every 100 iteration. In your documentation until 1000 iteration, but i want in every 100 iteration.

[devphilno]

@yjdeveloper have you figured out how to downscale the mAP calculation to a shorter interval?

[fcakyon]

@yjdeveloper @snphnolt use this version with -map 0.02 for map calculation at every 0.02 epoch (starts after warmup iterations)

https://github.com/fcakyon/darknet

[neso613]

mAP-chart

Where this map graph has seen?

[neso613]

I have followed the steps given by Mr. @AlexeyAB and got the red line but my problem is how to plot a mAP after every 100 iteration. In your documentation until 1000 iteration, but i want in every 100 iteration.

How do you got the red line?

[ghost]

@AlexeyAB

I am using your repo to detect a custom objects using yolov3. however I have get in to trouble. The predictions.jpg image do not draw the confidence score but it draws the class id.

i traced the image.c code and I have found that in the function definition

void draw_detections_v3(image im, detection *dets, int num, float thresh, char names, image alphabet, int classes, int ext_output)

how to resolev e the issue?

[ghost]

please, anyone, help. which function I have to use in AlexeyAB yolo repository in order to get confidence score drawings on the predictions.jpg image file???? I have get only class Id using this

!./darknet detector test data/trainer.data cfg/yolov3.cfg backup/yolov3_last.weights -thresh 0.1 -iou_thresh 0.3 data/img/tb500.jpg

[Leprechault]

You can use repo https://github.com/AlexeyAB/darknet that shows Loss & mAP chart during Training:

The command ./darknet detector demo ... -json_port 8070 -mjpeg_port 8090 works very well, but is there any way to save the image in vectorial format like eg. pdf, svg, *ps?

[Leprechault]

I found one solution here : https://github.com/Jumabek/darknet_scripts/#how-to-plot-yolo-loss

You basically need to save the output of ./darknet detector train <> into a log file and then python plot_yolo_log.py log_file.log

Note that the plot does not show in a jupyter-notebook even with %matplotlib inline. A work around is to copy all plot related code from https://github.com/Jumabek/darknet_scripts/blob/master/plot_yolo_log.py into a new function.

@rbarman in the log.txt output what's the information about mAP?

[ak3509311]

How to save the loss graph on drive because i run the code on colab .

[harshkc03]

I'm training Yolov3-tiny on colab using the following command- !./darknet detector train /content/obj.data /content/yolov3-tiny-obj.cfg backup/yolov3-tiny-obj_last.weights -dont_show -mjpeg_port 8090 -map

It shows MJPEG-stream sent in the output after every iteration and i know we have to use http://ip-address:8090 format to access the chart, but I'm unable to find the ip-address of my colab notebook. I tried using addresses from !ifconfig and !curl ipecho.net/plain but still no result. Any help would be appreciated.

[himewel]

@harshkc03 I found this quote in StackOverflow. I still not found a way to propagate the json and graph at same time, but you can try something like this to train and see your graph updating. It prints a url that you can access your loss graph with the follow commands:

!wget https://bin.equinox.io/c/4VmDzA7iaHb/ngrok-stable-linux-amd64.zip
!unzip ngrok-stable-linux-amd64.zip

get_ipython().system_raw('./ngrok http 8090 &')

!curl -s http://localhost:4040/api/tunnels | python3 -c \
 "import sys, json; print(json.load(sys.stdin)['tunnels'][0]['public_url'])"

After this, start your training:

!./darknet detector train /content/obj.data /content/yolov3-tiny-obj.cfg backup/yolov3-tiny-obj_last.weights -dont_show -mjpeg_port 8090 -map

[francismontalbo]

Is there a way to produce the loss curve and mAP from an existing weight?

[harshkc03]

@francismontalbo you can obtain mAP of the existing weight using the command- ./darknet detector map data/obj.data yolo-obj.cfg backup\yolo-obj_last.weights but you cannot generate the loss curve of an existing weight. Loss curve generates only during training.

[francismontalbo]

@francismontalbo you can obtain mAP of the existing weight using the command-

./darknet detector map data/obj.data yolo-obj.cfg backup\yolo-obj_last.weights

but you cannot generate the loss curve of an existing weight. Loss curve generates only during training.

Yes, I've been using that. I see, thank you for the response good sir.

[wc1997]

You can use pyngrok python package to display loss graph

!pip install pyngrok
from pyngrok import ngrok# Open a HTTP tunnel on port 8090
public_url = ngrok.connect(port = '8090')

public_url

Then run your training with flags

-mjpeg_port 8090 -map

[harshkc03]

You can use pyngrok python package to display loss graph

!pip install pyngrok
from pyngrok import ngrok# Open a HTTP tunnel on port 8090
public_url = ngrok.connect(port = '8090')

public_url

Then run your training with flags

-mjpeg_port 8090 -map

Thankyou sir, it works as expected.

[himewel]

You can use pyngrok python package to display loss graph

!pip install pyngrok
from pyngrok import ngrok# Open a HTTP tunnel on port 8090
public_url = ngrok.connect(port = '8090')

public_url

Then run your training with flags

-mjpeg_port 8090 -map

Seems much more elegant than my response, ty auhdsuahsduahs

[vishnuvardhan58]

Hello , I am getting the following error while using the command "!./darknet detector train data/obj.data cfg/yolov3_custom.cfg darknet53.conv.74 -dont_show -mjpeg_port 8090 -map".I am using google colab.

The connection to http://d80c91c46410.ngrok.io was successfully tunneled to your ngrok client, but the client failed to establish a connection to the local address localhost:8090.

Make sure that a web service is running on localhost:8090 and that it is a valid address.

The error encountered was: dial tcp 127.0.0.1:8090: connect: connection refused

[sercangokturk]

I have followed the steps given by Mr. @AlexeyAB and got the red line but my problem is how to plot a mAP after every 100 iteration. In your documentation until 1000 iteration, but i want in every 100 iteration.

Did you find a solution? Thanks in advance.

[shawntyshawny]

You can use repo https://github.com/AlexeyAB/darknet that shows Loss & mAP chart during Training:

I've followed this tutorial but my output mAP seems to have started its line from 68% and there is a broken line between 0 - 68%, how do I resolve this?

[Doomleet]

You can use repo https://github.com/AlexeyAB/darknet that shows Loss & mAP chart during Training:

Hello! It is work only on Windows? I dont know how use it on Linux. I use tag -map

[Doomleet]

You can use repo https://github.com/AlexeyAB/darknet that shows Loss & mAP chart during Training:

Hello! It is work only on Windows? I dont know how use it on Linux. I use tag -map

Ok, i do make without OPENCV=1, now i do make with OPENCV=1 and its work :)

[mhdayub]

how to show red line (percentage) and run on what file?

[oo92]

What is the y-axis? What do those numbers on the y-axis represent?

[khinmaunghtay4ah]

how to show red line (percentage) and run on what file?

@mhdayub You just have to add -map flag at the end of the command used for training and you will see accuracy-mAP during training.

For e.g, darknet.exe detector train data/obj.data cfg/yolov4-obj.cfg backup/yolov4-obj_last.weights -map

[hainguyen201]

go to darket folder, you will see the chart image file 'chart.png'

[DikshitV]

Hi, I am new to yolo. Where can I find the training loss values stored in the darknet? Is the training loss values stored or they are just directly plotted?

[ZaynAlk]

Hi, I am new to yolo. Where can I find the training loss values stored in the darknet? Is the training loss values stored or they are just directly plotted?

Go to darknet folder and you can find it there

[yeonmnim]

@AlexeyAB Hi all, i am using the colab to run yolov4 on my custom data, but now it seems like the mAP does not coming out for me. I previously can get the loss graph with a mAP line graph but that was long time ago. So, i have write a txt file to store the log, but it seems like when reaching 1000th iterations, the mAP cannot be calculated. It outputs me the error as shown below :

cuDNN status Error in: file: ./src/convolutional_kernels.cu : () : line: 543 : build time: Apr 2 2023 - 12:39:35

cuDNN Error: CUDNN_STATUS_BAD_PARAM Darknet error location: ./src/dark_cuda.c, cudnn_check_error, line #204 cuDNN Error: CUDNN_STATUS_BAD_PARAM: Success

and, is there any method to avoid the runtime to get stopped? i have 6000th iterations to run , but it will automatically stops when it reaches 3000 iterations.