TypeError: int() can't convert non-string with explicit base

[laenix]

TypeError: int() can't convert non-string with explicit base

Input:

python train.py --img 640 --batch 16 --epochs 5 --data ./data/dataset/dataset.yaml --cfg ./models/yolov5s.yaml --weights ''

Output:

Traceback (most recent call last):
  File "D:\software\Python38\lib\threading.py", line 932, in _bootstrap_inner
    self.run()
  File "D:\software\Python38\lib\threading.py", line 870, in run
    self._target(*self._args, **self._kwargs)
  File "D:\yolov5\utils\plots.py", line 124, in plot_images
    colors = color_list()  # list of colors
  File "D:\yolov5\utils\plots.py", line 34, in color_list
    return [hex2rgb(h) for h in plt.rcParams['axes.prop_cycle'].by_key()['color']]
  File "D:\yolov5\utils\plots.py", line 34, in <listcomp>
    return [hex2rgb(h) for h in plt.rcParams['axes.prop_cycle'].by_key()['color']]
  File "D:\yolov5\utils\plots.py", line 32, in hex2rgb
    return tuple(int(h[1 + i:1 + i + 2], 16) for i in (0, 2, 4))
  File "D:\yolov5\utils\plots.py", line 32, in <genexpr>
    return tuple(int(h[1 + i:1 + i + 2], 16) for i in (0, 2, 4))
TypeError: int() can't convert non-string with explicit base

Environment

If applicable, add screenshots to help explain your problem.

• OS: [Windows 10]
• GPU [1660 super]

Additional context

def color_list():
    # Return first 10 plt colors as (r,g,b) https://stackoverflow.com/questions/51350872/python-from-color-name-to-rgb
    def hex2rgb(h):
        return tuple(int(h[1 + i:1 + i + 2], 16) for i in (0, 2, 4))

    return [hex2rgb(h) for h in plt.rcParams['axes.prop_cycle'].by_key()['color']]

[github-actions]

👋 Hello @laenix, 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.

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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):

• Google Colab Notebook with free GPU:
• Kaggle Notebook with free GPU: https://www.kaggle.com/models/ultralytics/yolov5
• Google Cloud Deep Learning VM. See GCP Quickstart Guide
• Docker Image https://hub.docker.com/r/ultralytics/yolov5. See Docker Quickstart Guide

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[laenix]

[glenn-jocher]

@laenix thanks for the bug report. What version of matplotlib are you using?

import matplotlib

print(matplotlib.__version__)