ultralytics / yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
https://docs.ultralytics.com
GNU Affero General Public License v3.0
51.26k stars 16.44k forks source link

MAP NOT PRINTING #2283

Closed bobbilichandu closed 3 years ago

bobbilichandu commented 3 years ago

I started finetuning yolov5s with a private dataset, with opt evolve, multiscale. Map is not printing on the terminal

 Epoch   gpu_mem       box       obj       cls     total   targets  img_size
     0/299     0.73G    0.1458     0.041         0    0.1868        20       352: 100%|███████████████████████████████████████████████| 405/405 [01:57<00:00,  3.45it/s]

     Epoch   gpu_mem       box       obj       cls     total   targets  img_size
     1/299    0.575G    0.1261   0.05978         0    0.1858        65       544: 100%|███████████████████████████████████████████████| 405/405 [01:13<00:00,  5.50it/s]

     Epoch   gpu_mem       box       obj       cls     total   targets  img_size
     2/299    0.774G    0.1233   0.06626         0    0.1895        53       416: 100%|███████████████████████████████████████████████| 405/405 [01:09<00:00,  5.81it/s]

     Epoch   gpu_mem       box       obj       cls     total   targets  img_size
     3/299     4.24G    0.1201   0.06881         0    0.1889       164       544: 100%|███████████████████████████████████████████████| 405/405 [01:09<00:00,  5.81it/s]

     Epoch   gpu_mem       box       obj       cls     total   targets  img_size
     4/299    0.554G    0.1186   0.07062         0    0.1893        82       672: 100%|███████████████████████████████████████████████| 405/405 [01:11<00:00,  5.68it/s]

     Epoch   gpu_mem       box       obj       cls     total   targets  img_size
     5/299     4.16G     0.118   0.07071         0    0.1887        80       672: 100%|███████████████████████████████████████████████| 405/405 [01:08<00:00,  5.93it/s]

     Epoch   gpu_mem       box       obj       cls     total   targets  img_size
     6/299    0.568G    0.1163   0.06736         0    0.1836        48       576: 100%|███████████████████████████████████████████████| 405/405 [01:12<00:00,  5.58it/s]

     Epoch   gpu_mem       box       obj       cls     total   targets  img_size
     7/299     4.01G    0.1161   0.07131         0    0.1874        56       352: 100%|███████████████████████████████████████████████| 405/405 [01:09<00:00,  5.82it/s]

     Epoch   gpu_mem       box       obj       cls     total   targets  img_size
     8/299     4.03G     0.116   0.07146         0    0.1874        30       416: 100%|███████████████████████████████████████████████| 405/405 [01:07<00:00,  5.96it/s]

     Epoch   gpu_mem       box       obj       cls     total   targets  img_size
     9/299     4.03G    0.1153   0.07128         0    0.1865       199       352: 100%|███████████████████████████████████████████████| 405/405 [01:09<00:00,  5.83it/s]

     Epoch   gpu_mem       box       obj       cls     total   targets  img_size
    10/299     2.83G    0.1152    0.0714         0    0.1866        36       608: 100%|███████████████████████████████████████████████| 405/405 [01:10<00:00,  5.75it/s]

     Epoch   gpu_mem       box       obj       cls     total   targets  img_size
    11/299    0.786G    0.1153   0.07282         0    0.1881       152       384: 100%|███████████████████████████████████████████████| 405/405 [01:09<00:00,  5.84it/s]

     Epoch   gpu_mem       box       obj       cls     total   targets  img_size
    12/299     4.07G    0.1143   0.07729         0    0.1916       474       800:  37%|█████████████████▏                             | 148/405 [00:24<00:44,  5.80it/s]

How to check map now? Is there any mistake in my training? Any help would be appreciated. Thanks in advance.

github-actions[bot] commented 3 years ago

👋 Hello @chandu1263, 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.

If this is a 🐛 Bug Report, please provide screenshots and minimum viable code to reproduce your issue, otherwise we can not help you.

If this is a custom training ❓ Question, please provide as much information as possible, including dataset images, training logs, screenshots, and a public link to online W&B logging if available.

For business inquiries or professional support requests please visit https://www.ultralytics.com or email Glenn Jocher at glenn.jocher@ultralytics.com.

Requirements

Python 3.8 or later with all requirements.txt dependencies installed, including torch>=1.7. To install run:

$ pip install -r requirements.txt

Environments

YOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):

Status

CI CPU testing

If this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training (train.py), testing (test.py), inference (detect.py) and export (export.py) on MacOS, Windows, and Ubuntu every 24 hours and on every commit.

bobbilichandu commented 3 years ago

Weights are not being saved as well

glenn-jocher commented 3 years ago

@chandu1263 that's correct. --evolve does not test every epoch nor save any weights. I would recommend you see the hyperparameter evolution tutorial:

Tutorials

github-actions[bot] commented 3 years ago

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.