borutb-fri / fmld Goto Github PK

issue 1. I'm using tensorflow object detection API and I receive an error with your dataset because of an unwanted class label in the data. error happens when using the tf records generating script as follows

python Tensorflow/scripts/generate_tfrecord.py -x Tensorflow/workspace/images/FMLD_cleaned_dataset/test -l Tensorflow/workspace/annotations/label_map.pbtxt -o Tensorflow/workspace/annotations/test.record -c Tensorflow/workspace/annotations/csv_train.csv

File "Tensorflow/scripts/generate_tfrecord.py", line 101, in class_text_to_int
return label_map_dict[row_label]
KeyError: 'invalid_face'

I used my own python script to make a 1->1 mapping from your provided "FMLD_annotations" folder with xml files as the labels, into the full dataset of combined WIDER and MAFA datasets containing all the images. The mapping was done on the basis of identifying the matching filenames of the xml files and the jpg images. As I dont have matlab on my own computer.

How many classes does the dataset contain, it seems to be more than these three, which I put into my labelmap.pbtxt in tensorflow
with mask (name: masked_face),
without mask (name: unmasked_face) and
with mask worn incorrectly (name: incorrectly_masked_face).

issue 2. Does your dataset have bounding box coordinates in the precision of "even numbered floats" because I saw that the bounding box coordinates are given as float instead of the typical int, so that a banker's round shouldnt be necessary?
many coordinates were given like 919.0

issue 3. This was something that I noticed when inspecting the WIDERFACE dataset images. That you sourced some of your dataset from. There was some really obscene and bizarre category of "car accident" and "streetfight" images in the WIDERFACE dataset. I just wanted to make a note about it that those could be less than ethical images in terms of research. I deleted those categories of pictures from my dataset.

issue 1: These was not necessarily the only bad data I found. But it was what I found from my dataset when I inspected the csv file, after having gotten crash from illegal bounding box outside image dimensions.

File "C:\Users\lauri\anaconda3\envs\tf_kaggle\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 154, in Assert
raise errors.InvalidArgumentError(
tensorflow.python.framework.errors_impl.InvalidArgumentError: Expected 'tf.Tensor(False, shape=(), dtype=bool)' to be true. Summarized data: b'maximum box coordinate value is larger than 1.100000: '
1.1067415

The ones I found from my subset of your FMLD dataset with sketchy bbox coordinates were these in csv

filename
test_00000749.jpg
test_00001127.jpg
test_00001586.jpg
test_00001607.jpg
test_00001626.jpg
test_00001626.jpg
test_00003030.jpg
test_00003055.jpg
test_00003672.jpg
test_00003750.jpg
test_00003774.jpg
test_00004007.jpg
test_00004179.jpg
 
filename
train_00000019.jpg

INVALID_COORDINATES_excelsheet_test_train.xlsx

Issue 2: I found Hitler the dataset. I think he was maybe hiding in the WIDERFACE.
picture name
0_Parade_Parade_0_914.jpg
But I managed to delete him from my dataset as well :)