Where can I get the yolo.h5 file? about deeplearning.ai HOT 23 CLOSED

So I found the solution:

The yolo.h5 file can be generated using the YAD2K repository here: https://github.com/allanzelener/YAD2K

Steps how to do it on windows:

• Clone the above repository to your computer

• Download the yolo.weights file from here: http://pjreddie.com/media/files/yolo.weights

• Download the yolo.cfg file form here: https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolo.cfg

• Copy the downloaded weights and cfg files to the YAD2K master directory

Run python yad2k.py yolo.cfg yolo.weights model_data/yolo.h5 on the shell and the h5 file will be generated.

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Just go to Yolo website and download it
https://pjreddie.com/darknet/yolo/

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@miranthajayatilake the link for yolo.cfg not worked.

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You can get the weights and cfg file from this website.
https://pjreddie.com/darknet/yolo/

The coursera course is using YOLOv2 608 x 608. You will need tensoflow v1 to compile.

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I get a error message when I run yad2k.py
"Traceback (most recent call last):
File "yad2k.py", line 270, in
_main(parser.parse_args())
File "yad2k.py", line 156, in _main
buffer=weights_file.read(weights_size * 4))
TypeError: buffer is too small for requested array "
Any suggestions?

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Thanks it helped 👍

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Use this one:
https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov1.cfg

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• https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/

@miranthajayatilake , I am not able to download the configuration file? the link isn't valid! Also, does the Yolo weight corresponds to version2 or version 3?

from deeplearning.ai.

So I found the solution:

The yolo.h5 file can be generated using the YAD2K repository here: https://github.com/allanzelener/YAD2K

Steps how to do it on windows:

• Clone the above repository to your computer
• Download the yolo.weights file from here: http://pjreddie.com/media/files/yolo.weights
• Download the yolo.cfg file form here: https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolo.cfg
• Copy the downloaded weights and cfg files to the YAD2K master directory

Run python yad2k.py yolo.cfg yolo.weights model_data/yolo.h5 on the shell and the h5 file will be generated.

from deeplearning.ai.

Can anyone explain this step. I have downloaded both cfg and weight file. I don't understand where and how to run it?

Run python yad2k.py yolo.cfg yolo.weights model_data/yolo.h5 on the shell and the h5 file will be generated.

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Folks, this code is from deeplearning.ai/ and you can sign up for their free course and work this out.

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Can anyone explain this step. I have downloaded both cfg and weight file. I don't understand where and how to run it?

Run python yad2k.py yolo.cfg yolo.weights model_data/yolo.h5 on the shell and the h5 file will be generated.
@Sameedquais
you should run in command prompt or Anaconda prompt with same directory as YAD2K master.

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how can i run it in google colab?

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how can i run it in google colab?

1. Clone repo using !git clone https://github.com/allanzelener/YAD2K.git
2. Go inside the directory using os.chdir(folder_name)
3. Get the weights with:

!wget https://pjreddie.com/media/files/yolov2-voc.weights
!wget https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov2-voc.cfg

3. Run !python3 yad2k.py yolov2-voc.cfg yolov2-voc.weights model_data/yolov2-voc.h5

Tip: To run any terminal command on colab you can use ! before the command. Refer this

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I get a error message when I run yad2k.py
"Traceback (most recent call last):
File "yad2k.py", line 270, in
_main(parser.parse_args())
File "yad2k.py", line 156, in _main
buffer=weights_file.read(weights_size * 4))
TypeError: buffer is too small for requested array "
Any suggestions?

Hi, we must make yolo.cfg and yolo.weights have the same version, yolo having many versions like yolo-tiny,yolov1,yolov2,yolov3....

from deeplearning.ai.

You can get the weights and cfg file from this website.
https://pjreddie.com/darknet/yolo/

The coursera course is using YOLOv2 608 x 608. You will need tensoflow v1 to compile.

Hi, but to degrade tensorflow to v1, yolo.utils is using keras which needs tf v>2.0 then how to proceed? and while using yolov2 h5 file in tf version 2.4.0, its giving error "yad2k.models.keras_yolo is not loaded, but a Lambda layer uses it. It may cause errors." while loading model. any suggestions please?

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Can anyone explain this step. I have downloaded both cfg and weight file. I don't understand where and how to run it?

Run python yad2k.py yolo.cfg yolo.weights model_data/yolo.h5 on the shell and the h5 file will be generated.
Could you help me how to copy cfg and weigth file on master directory in google colab? I got error when I want to run python yad2k.py yolo.cfg yolo.weights model_data/yolo.h5 on the shell and the h5

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thank you

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anybody have a pre trained yolo 1 weight.h5 file ?

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I get a error message when I run yad2k.py
"Traceback (most recent call last):
File "yad2k.py", line 270, in
_main(parser.parse_args())
File "yad2k.py", line 156, in _main
buffer=weights_file.read(weights_size * 4))
TypeError: buffer is too small for requested array "
Any suggestions?

Hi, we must make yolo.cfg and yolo.weights have the same version, yolo having many versions like yolo-tiny,yolov1,yolov2,yolov3....

I have the same version, it is still showing this error

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for anyone who still has this problem in tensorflow 2,go to original website of yolov2 and download darknet and weights file,find yolo config in darknet folder, then using yad2k you can easily generate .h5 file,(when running yad2k.py you get bunch of import errors that you have to manually correct them because of new version of tensorflow)
yolo v2site:
https://pjreddie.com/darknet/yolov2/
installing yad2k:
git clone https://github.com/allanzelener/yad2k.git
put config and weight file inside yad2k folder
if you get space_to_depth err, go to the corresponding line and change it to tf.nn.space_to_depth

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I am getting the following error:

Loading weights.
Weights Header: [ 0 1 0 32013312]
Parsing Darknet config.
Traceback (most recent call last):
File "C:\Users\tsoam\Downloads\YAD2K\yad2k.py", line 274, in
_main(parser.parse_args())
File "C:\Users\tsoam\Downloads\YAD2K\yad2k.py", line 95, in _main
cfg_parser.read_file(unique_config_file)
File "C:\Users\tsoam\AppData\Local\Programs\Python\Python311\Lib\configparser.py", line 733, in read_file
self._read(f, source)
File "C:\Users\tsoam\AppData\Local\Programs\Python\Python311\Lib\configparser.py", line 1100, in _read
raise MissingSectionHeaderError(fpname, lineno, line)
configparser.MissingSectionHeaderError: File contains no section headers.

Note: I have already manually corrected import statements as I am using tf 2.13, Python version 3.11.

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I am getting the following error:

Loading weights. Weights Header: [ 0 1 0 32013312] Parsing Darknet config. Traceback (most recent call last): File "C:\Users\tsoam\Downloads\YAD2K\yad2k.py", line 274, in _main(parser.parse_args()) File "C:\Users\tsoam\Downloads\YAD2K\yad2k.py", line 95, in _main cfg_parser.read_file(unique_config_file) File "C:\Users\tsoam\AppData\Local\Programs\Python\Python311\Lib\configparser.py", line 733, in read_file self._read(f, source) File "C:\Users\tsoam\AppData\Local\Programs\Python\Python311\Lib\configparser.py", line 1100, in _read raise MissingSectionHeaderError(fpname, lineno, line) configparser.MissingSectionHeaderError: File contains no section headers.

Note: I have already manually corrected import statements as I am using tf 2.13, Python version 3.11.

I solved this by directly downloading yolov2.cfg from GitHub repo rather than using curl. I think curl messes up the format of the file.

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