Comments (11)
@sudonto I didn't get any div by zero errors and don't really understand why its happening for you, but you can try re cloning the repo and do the changes I mentioned in #27 and it should work. Also, my loss was even bigger. It was around 500 after 200 epochs and around 400 after 2000 epochs. Furthermore, in tensorboard, I could see that my model was over fitting. Instead of working on SSDs, which I was even testing in the first place as an alternative to Faster RCNNs, I would rather put my effort on YOLO v2. Anyway, am currently involved in a different project but if I do find a good SSD implementation, I will post it here.
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Can someone please specify the arguments to pass to the mergeAnnotationFiles.py for doing this?
While the pwd
being the $LISA/tools
directory of the dataset I tried:
python mergeAnnotationFiles.py frame mergeAnnotations.csv ../
python mergeAnnotationFiles.py frame mergeAnnotations.csv ../aiua120214-0/frameAnnotations-DataLog02142012_external_camera.avi_annotations
python mergeAnnotationFiles.py video mergeAnnotations.csv ../aiua120214-0/frameAnnotations-DataLog02142012_external_camera.avi_annotations
but the output always comes: No annotation files found, exiting...
please help me out.
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Okay I found a way of at least running the mergeAnnotationFiles.py.
I copied it to the $LISA
folder and ran the following code:
python mergeAnnotationFiles.py frame mergeAnnotations.csv
this merged all the annotations from frames present at any sub directory of the $LISA
directory. But I still cannot find a way to merge only annotations of stop signs and pedestrian crossing signs.
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I think we have to modify mergeAnnotation.py such that only signs we want to put in csv file.
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@sudonto if you were able to filter only stop and pedestrian signs please tell how you did it.
I am currently able to extract only pedestrian and stop signs using:
python extractAnnotations.py -f stopAhead -f pedestrianCrossing copy ../allAnnotations.csv
this creates a folder named annotations which will contain all the pics where pedestrianCrossing and stopAhead signs are available.
But I am still unable to build the annotations for them
I even tried:
python mergeAnnotationFiles.py frame mergedAnnotations.csv annotations/
still I find that the mergedAnnotations.csv is the same as allAnnotations.csv
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I will let you know soon I have the solution.
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Hey @YashBansod ,
I was able to build only stop sign and pedestriancrosssing sign into one csv file. In my case, I use filterAnnotationFile.py first to generate those signs into seperate folder and then execute mergeAnnotationFiles.py to combine 2 csv file (stop and pedestrian sign) into one file.
Please try.
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Hi @sudonto
Sorry for the late reply. I was able to get this thing working. In issue #21 steps mentioned by @jacksmith21 are sufficient to run get the code working. the mergeAnnotationFiles.py just merges all the annotations in all the sub-directories, but the dataprep.py handles the seperation of the pedestrian and stop sign images. The documentation of this was a bit misleading, causing a lot of my time to be wasted just on figuring on how to make this work. Anyway the output was not satisfactory for my application and I couldn't replicate the outputs mentioned in the readme of this repository, so I started looking elsewhere.
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Yes, you absolutely correct about this. I started to analyze each code of dataprep.py week ago and I found that there is a line of code that filters out the annotation tag other than the desired signs.
Now, I have 2 problems afterward: my loss function is very large (arround 200 after 200 epochs) and the produced model always give me an error in inference mode (division by zero when calculating the IoU, sighhh).
I think I'd like to search for another SSD algorithms.
PS.: In case you find another robust SSD algorithm yet offer simple code, would you mind to share with me? :)
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@sudonto were you able to run the python inference.py -m demo
with the pre-trained model provided by the creator of this repo?
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Yes, I was able to run python inference.py -m demo
with success using pre-trained model, showing images in sample_images folder with bounding box (no division by zero).
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Related Issues (20)
- image not getting saved in inference_out
- error when run
- TypeError: Expected int32, got list containing Tensors of type '_Message' instead. HOT 6
- Error when run inference.py HOT 2
- About mergedAnnotations.csv
- Improve the effect?
- loss when end training HOT 1
- Help me out~ HOT 1
- 按照LISA交通标志数据集中的说明创建'mergedAnnotations.csv',以便仅显示停车标志和人行横道标志
- accuracy 怎么写呢
- The use of the DEFAULT BOX
- please help me, i am stuck in running inference.py HOT 1
- why USE
- Why use Alexnet instead of VGG?
- Exception running inference.py HOT 2
- ValueError: Dimension 1 in both shapes must be equal, but are 1152 and 288. Shapes are [?,1152] and [?,288]. From merging shape 2 with other shapes. for 'concat/concat_dim' (op: 'Pack') with input shapes: [?,17856], [?,4140], [?,1152], [?,288]. HOT 2
- I have a probelm running inference.py -m demo HOT 1
- This model doesn't predict on new images?
- where are the extractAnnotations.py and mergeAnnotationFiles.py? HOT 1
- This model doesn't predict on new images?
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