When I run pyodi ground-truth ../instances_train2017.json according to the tutorial, the results are not displayed or saved, and the code does not report errors. The following are the results:

2021-08-27 21:57:18.223 | INFO     | pyodi.core.utils:coco_ground_truth_to_df:38 - Loading Ground Truth File
2021-08-27 21:57:18.302 | INFO     | pyodi.core.utils:coco_ground_truth_to_df:48 - Converting COCO Ground Truth to pd.DataFrame
2021-08-27 21:57:18.418 | INFO     | pyodi.plots.common:plot_scatter_with_histograms:61 - Plotting Scatter with Histograms
2021-08-27 21:57:18.735 | INFO     | pyodi.plots.common:plot_scatter_with_histograms:61 - Plotting Scatter with Histograms

@mmeendez8 @igonro @cgiraldo thanks a lot for this awesome package!

pycocotools-fix package currently doesnt work on windows: https://github.com/junjuew/cocoapi/pull/4

official pycocotools package is constantly updated by the facebook research team: https://pypi.org/project/pycocotools/

by accepting this pr, pyodi package will be supported on windows.

I am attempting to merge 2 coco format file with pyodi and i cannot get it to work at all.

The command I am running: pyodi coco merge result.json studio_test_val.json output.json

The error I am getting: Traceback (most recent call last):

  File "/home/christ/miniconda3/envs/label-studio/bin/pyodi", line 5, in <module>
    from pyodi.cli import app
  File "/home/christ/miniconda3/envs/label-studio/lib/python3.9/site-packages/pyodi/cli.py", line 5, in <module>
    from pyodi.apps.evaluation import evaluation
  File "/home/christ/miniconda3/envs/label-studio/lib/python3.9/site-packages/pyodi/apps/evaluation.py", line 39, in <module>
    from pycocotools.cocoeval import COCOeval
  File "/home/christ/miniconda3/envs/label-studio/lib/python3.9/site-packages/pycocotools/cocoeval.py", line 7, in <module>
    from . import mask as maskUtils
  File "/home/christ/miniconda3/envs/label-studio/lib/python3.9/site-packages/pycocotools/mask.py", line 3, in <module>
    import pycocotools._mask as _mask
  File "pycocotools/_mask.pyx", line 1, in init pycocotools._mask
ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 96 from C header, got 88 from PyObject

Please help me with this issue. Thank you.

Fixes kaleido permission err:

PermissionError: [Errno 13] Permission denied: '/home/mmendez/anaconda3/envs/pyodi/lib/python3.7/site-packages/kaleido-0.1.0-py3.7-linux-x86_64.egg/kaleido/executable/kaleido'

Code to reproduce:

    image_0[
        int(image_0_bbox_top) : int(image_0_bbox_top + image_0_bbox_height),
        int(image_0_bbox_left) : int(image_0_bbox_left + image_0_bbox_width),
    ] = 0

Output:

flake8...................................................................Failed
- hook id: flake8
- exit code: 1

tests/apps/test_paint_annotations.py:137:30: E203 whitespace before ':'

Black is adding extra whitespaces that do not match with flake8 config

The way image_id is currently updated only works when all the jsons contain image_ids filling all the range [0, N).

If any of the jsons start it's image_id at other number or some image_id is missing from the range, the results are incorrect.

Use https://github.com/warner/python-versioneer for version control.

Follow setup: https://jacobtomlinson.dev/posts/2020/versioning-and-formatting-your-python-code/

Currently, when using pyodi paint-annotations each of the bounding boxes is painted with a random color:

https://github.com/pyodi/pyodi/blob/master/pyodi/apps/paint_annotations.py#L83

It would be a desirable feature to make this behaviour optional and allow the user to specify different coloring options. For example:

• Constant color. Use same color for all annotations.
• Color by key (property inside each annotation dictionary; i.e. category_id). Use same color for annotations sharing the same key.

Example content of annotation:

{
    "image_id": 0,
    "bbox": [704.2313842773438, 441.23284912109375, 15.76861572265625, 16.6729736328125],
    "score": 0.7878580093383789, 
    "category_id": 1
}

Right now the histograms have the same color, so the appearance of the legend is a little bit weird.

It would be nice if both histograms have different colors. The colors should be also different from the default plotly color sequence (More info: https://plotly.com/python/discrete-color/#color-sequences-in-plotly-express)

Input:

pip install pyodi
pyodi coco merge 1.json 2.json output.json

Output:

ValueError: numpy.ndarray size changed, may indicate binary incompatibility

When you run this code, the error will be fixed.

pip install numpy==1.23.5

I want to get the anchor setting of my dataset, the example you showed is as follows: pyodi train-config generation \ $TINY_COCO_ANIMAL/annotations/train.json \ --input-size [1280,720] \ --n-ratios 3 --n-scales 3

However, for Faster R-CNN, the size of input image is not fixed, in this case, how should I set the ' --input-size'?

The readme states Pyodi can help you to automatically design a set of anchors that fit your data distribution can you provide an example or reference that describes this process, and how the visualisations relate? Many thanks

Excuse me, I want to know how clustering is done. I don't see the call of core/clustering.py in the place where the plot is drawn? Did I understand it wrong?

The current plots analyze the images and bounding boxes separately. There is some important insights missing that need to combine both sources of information. For example:

• Total Area occupied by bounding boxes in each image.
• Number of bounding boxes per image.
• Mean distance between bounding box centroids per image.