Testing issue about piepredict HOT 10 CLOSED

Hi @Marouene-Oueslati,
Try adding the line

imdb.extract_and_save_images(extract_frame_type='annotated')

after line 56 (imdb = PIE(data_path=pie_path)) in train_test.py. This should extract the images. You will need 1.1 Tb of space to hold all images from the dataset with annotations. If you are not planning to use training and validation data, you can modify the function pie_data.py:extract_and_save_images() to extract images only from set03 (test data).

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Hi @ykotseruba ,
i'm trying to extract only from set01 as test data, the following issues appear on the command line when python train_test.py 1 runs:

Generating train features crop_type=context crop_mode=pad_resize
save_path=./data/data\pie\train\features_context_pad_resize\vgg16_none,
[--------------------] 0.00% Traceback (most recent call last):
  File "train_test.py", line 178, in <module>
    main(train_test=train_test)
  File "train_test.py", line 171, in main
    intent_model_path = train_intent(train_test=train_test)
  File "train_test.py", line 149, in train_intent
    data_opts=data_opts)
  File "C:\Users\Jar\object_detection\PIEPredict\pie_intent.py", line 550, in train
    data_subset = 'train'))
  File "C:\Users\Jar\object_detection\PIEPredict\pie_intent.py", line 242, in load_images_and_process
    set_id = imp.split('/')[-3]
IndexError: list index out of range

could you please help me with this? Thanks!

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Hi @RoteOrange,
The error is likely caused by path formatting: paths in Windows are separated with \ and in Linux with /. To fix this you can try changing imp.split('/') to imp.split('\').
In general, it is better to run the code on Ubuntu where it was tested. Unfortunately, I don't have access to a Windows machine, so if there are other Windows-specific issues, I won't be able to help.

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Hi @Marouene-Oueslati,
Try adding the line

imdb.extract_and_save_images(extract_frame_type='annotated')

after line 56 (imdb = PIE(data_path=pie_path)) in train_test.py. This should extract the images. You will need 1.1 Tb of space to hold all images from the dataset with annotations. If you are not planning to use training and validation data, you can modify the function pie_data.py:extract_and_save_images() to extract images only from set03 (test data).

Hi @ykotseruba ,
Thanks a lot for your answer. I have configured the right set of video clips.
That being said, do we need to use sh function "split_clips_to_frames.sh" to extract the needed images for the desired Set-XX beforehand as I still have the same issue.
Furthermore, I am wondering if the model could tested for any type of raw video without being linked to annotated images (I mean in Real Time application)
Thanks a lot for your valuable feedback

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Hi @Marouene-Oueslati,
split_clips_to_frames.sh extracts all frames, whereas the line of code I suggested extracts only the annotated frames (1/3 of all frames). If nothing else works, you may try using the bash script but it will require 3 times more memory.

To answer your second question, the model needs bounding boxes for pedestrians to work. In order to apply it to videos that are not part of dataset you will either have to annotate them manually or implement object detection/tracking. For evaluation you will also need other ground truth: intention scores, vehicle information, etc.

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Hi @ykotseruba ,
your feedback is highly appreciated. Indeed I do understand your feedback as the code as well as the paper was part of a deep research topic with in-house validation.
The line of code till now seems not working, perhaps I will try to extract it accordingly using the split_clips_to_frames.sh.

Just wondering if you have any idea regarding the use of yolo / ss to extract the bounding boxes & reshaping the BB convention.
My last question concerns the possibility of only training the intention model without linking it to trajectory prediction nor vehicle speed; if so, could you please share some rules or approach.
My apologies for the long message.

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Hi @Marouene-Oueslati,
Could you please be more specific? What error do you get when running the extract_and_save_images()?

Regarding two other questions, I didn't run object detectors on PIE so I can't help you with this. If you need annotations in YOLO or any other format you can use CVAT to convert them.
It is possible to train only the intent model. train_intent()' function has code for both training and testing. Try commenting out train_predict()intrain_test.py:173`, that should probably do it.

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Hello @ykotseruba; this is a screen shot of the error that I am getting when running the "python train_test.py 2". FYI, as you can see, I am only testing for video 0002 from the set01 and have added imdb.extract_and_save_images(extract_frame_type='annotated')

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Hi @Marouene-Oueslati,
Based on the error, the images aren't extracted. Do you get any output or errors from extract_and_save_images?

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Closing due to inactivity.

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