Open hardikchauhan8 opened 6 years ago
you need to put the full path to your annotation folder it seems like it cant find it
Yes, But can you explain how can I create that folder for my own dataset?
for each one of the images in the training set you should have an xml file for the annotation containing the bounding boxes of your object. you can use labelImg tool to create the annotation for the images
Okay thanks.
Is there any specific directory format i have to specify for annotation, if i have multiple classes?
You should make a dataset with two folders; one for annotation files and one for images. Each image needs a .xml file with VOC formatted annotations or the network will ignore and not train on that image.
Solved.
I had to put all the images in the root of images folder, If I create subfolders in the folder of images it is not working.
hy@hy-desktop:/devdata/AI/OD/darkflow$ flow --model cfg/yolo-pig.cfg --train --dataset "/JPEGImages" --annotation "/Annotations" --gpu 1.0 /usr/local/lib/python3.5/dist-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from
floatto
np.floatingis deprecated. In future, it will be treated as
np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
Parsing cfg/yolo-pig.cfg Loading None ... Finished in 0.0001862049102783203s
Building net ... Source | Train? | Layer description | Output size -------+--------+----------------------------------+--------------- | | input | (?, 416, 416, 3) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 416, 416, 32) Load | Yep! | maxp 2x2p0_2 | (?, 208, 208, 32) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 208, 208, 64) Load | Yep! | maxp 2x2p0_2 | (?, 104, 104, 64) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 104, 104, 128) Init | Yep! | conv 1x1p0_1 +bnorm leaky | (?, 104, 104, 64) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 104, 104, 128) Load | Yep! | maxp 2x2p0_2 | (?, 52, 52, 128) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 52, 52, 256) Init | Yep! | conv 1x1p0_1 +bnorm leaky | (?, 52, 52, 128) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 52, 52, 256) Load | Yep! | maxp 2x2p0_2 | (?, 26, 26, 256) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 26, 26, 512) Init | Yep! | conv 1x1p0_1 +bnorm leaky | (?, 26, 26, 256) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 26, 26, 512) Init | Yep! | conv 1x1p0_1 +bnorm leaky | (?, 26, 26, 256) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 26, 26, 512) Load | Yep! | maxp 2x2p0_2 | (?, 13, 13, 512) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 13, 13, 1024) Init | Yep! | conv 1x1p0_1 +bnorm leaky | (?, 13, 13, 512) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 13, 13, 1024) Init | Yep! | conv 1x1p0_1 +bnorm leaky | (?, 13, 13, 512) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 13, 13, 1024) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 13, 13, 1024) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 13, 13, 1024) Load | Yep! | concat [16] | (?, 26, 26, 512) Load | Yep! | local flatten 2x2 | (?, 13, 13, 2048) Load | Yep! | concat [26, 24] | (?, 13, 13, 3072) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 13, 13, 1024) Init | Yep! | conv 1x1p0_1 linear | (?, 13, 13, 30) -------+--------+----------------------------------+--------------- GPU mode with 1.0 usage cfg/yolo-pig.cfg loss hyper-parameters: H = 13 W = 13 box = 5 classes = 1 scales = [1.0, 5.0, 1.0, 1.0] Building cfg/yolo-pig.cfg loss Building cfg/yolo-pig.cfg train op 2018-01-25 16:01:57.509413: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX Finished in 14.746067762374878s
Enter training ... Error: Annotation directory not found /Annotations . `
when I run flow --model cfg/yolo-pig.cfg --train --dataset "./JPEGImages" --annotation "./Annotations" --gpu 1.0
It's sloved.
flow --model cfg/yolo-pig.cfg --train --dataset "./JPEGImages" --annotation "./Annotations" --gpu 1.0 /usr/local/lib/python3.5/dist-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from
floatto
np.floatingis deprecated. In future, it will be treated as
np.float64 == np.dtype(float).type`.
from ._conv import register_converters as _register_converters
Parsing cfg/yolo-pig.cfg Loading None ... Finished in 0.0002033710479736328s
Building net ... Source | Train? | Layer description | Output size -------+--------+----------------------------------+--------------- | | input | (?, 416, 416, 3) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 416, 416, 32) Load | Yep! | maxp 2x2p0_2 | (?, 208, 208, 32) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 208, 208, 64) Load | Yep! | maxp 2x2p0_2 | (?, 104, 104, 64) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 104, 104, 128) Init | Yep! | conv 1x1p0_1 +bnorm leaky | (?, 104, 104, 64) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 104, 104, 128) Load | Yep! | maxp 2x2p0_2 | (?, 52, 52, 128) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 52, 52, 256) Init | Yep! | conv 1x1p0_1 +bnorm leaky | (?, 52, 52, 128) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 52, 52, 256) Load | Yep! | maxp 2x2p0_2 | (?, 26, 26, 256) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 26, 26, 512) Init | Yep! | conv 1x1p0_1 +bnorm leaky | (?, 26, 26, 256) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 26, 26, 512) Init | Yep! | conv 1x1p0_1 +bnorm leaky | (?, 26, 26, 256) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 26, 26, 512) Load | Yep! | maxp 2x2p0_2 | (?, 13, 13, 512) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 13, 13, 1024) Init | Yep! | conv 1x1p0_1 +bnorm leaky | (?, 13, 13, 512) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 13, 13, 1024) Init | Yep! | conv 1x1p0_1 +bnorm leaky | (?, 13, 13, 512) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 13, 13, 1024) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 13, 13, 1024) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 13, 13, 1024) Load | Yep! | concat [16] | (?, 26, 26, 512) Load | Yep! | local flatten 2x2 | (?, 13, 13, 2048) Load | Yep! | concat [26, 24] | (?, 13, 13, 3072) Init | Yep! | conv 3x3p1_1 +bnorm leaky | (?, 13, 13, 1024) Init | Yep! | conv 1x1p0_1 linear | (?, 13, 13, 30) -------+--------+----------------------------------+--------------- GPU mode with 1.0 usage cfg/yolo-pig.cfg loss hyper-parameters: H = 13 W = 13 box = 5 classes = 1 scales = [1.0, 5.0, 1.0, 1.0] Building cfg/yolo-pig.cfg loss Building cfg/yolo-pig.cfg train op 2018-01-25 16:02:36.637526: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX Finished in 14.701897621154785s
Enter training ... `
@HardikChauhanSA hello. how did you able to correct the Enter training ... Error: Annotation directory not found train/Annotations error? Currently, it my problem. What did you change in flow --model cfg/tiny-yolo-voc-3c.cfg --load bin/tiny-yolo-voc.weights --train --annotation train/Annotations --dataset train/Images command? Thank you!
do you have annotation folder created containing the xml files for all of your images?
My mistake was that i have created sub folder in my dataset directory in you case train/images.
I have putted all the images to 'images' directory and it solved my issue.
On Thu, Mar 1, 2018 at 10:53 PM, aaseagrass notifications@github.com wrote:
@HardikChauhanSA https://github.com/hardikchauhansa hello. how did you able to correct the Enter training ... Error: Annotation directory not found train/Annotations error? Currently, it my problem. What did you change in flow --model cfg/tiny-yolo-voc-3c.cfg --load bin/tiny-yolo-voc.weights --train --annotation train/Annotations --dataset train/Images command? Thank you!
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@nightfox8 I have a video and its annotations as csv file, how can I use them to train my model?
Hello,
When I try to create a model with my custom dataset with two classes I am getting the below error,
I am trying to create a model with this command,
flow --model cfg/tiny-yolo-voc-3c.cfg --load bin/tiny-yolo-voc.weights --train --annotation train/Annotations --dataset train/Images