Need help with confusing dataset formats for Images and annotations The Next CEO of Stack Overflow2019 Community Moderator ElectionBest format for recording time stamp and GPSHow to prepare/augment images for neural network?Tools to perform SQL analytics on 350TB of csv dataAnimal Detection datasetFormat for time series data with non-trivial sampled dataHybrid Convolutional and Conventional Neural NetworksHow can I combine images for Matlab deep learning?Neural Network Architecture for Identifying Image CopiesHow to Build Mobile Application for Image Recognition?
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Need help with confusing dataset formats for Images and annotations
The Next CEO of Stack Overflow2019 Community Moderator ElectionBest format for recording time stamp and GPSHow to prepare/augment images for neural network?Tools to perform SQL analytics on 350TB of csv dataAnimal Detection datasetFormat for time series data with non-trivial sampled dataHybrid Convolutional and Conventional Neural NetworksHow can I combine images for Matlab deep learning?Neural Network Architecture for Identifying Image CopiesHow to Build Mobile Application for Image Recognition?
$begingroup$
I have a more general question, which I could not answer after quite a bit of google. Actually, I got more confused. I hope you can share some light.
I am familiar with deep learning, Keras but come from time series analysis and now start in image processing.
Background
What I noticed, that most tutorial use open datasets to explain implementations of CNNs. Each dataset (COCO, ImageNet, CIFAR,…) chooses all different formatting of the annotations and representation of the images.
For example, COCO just e.g. uses the name of the image in json while others use the flattened RGB information of the image in csv.
Now I want to create my own dataset with hand-gestures. Generally, I could just give each image one tag and be finished for image classification. However, I see many implementations of complex Network architectures like RetinaNet, which use formats such as COCOs also for object (here hand) recognition.
The Question(s):
Not knowing if I will later need more sophisticated annotations, should I start with a COCO format? But if so, which should I choose of the many formats? COCOs, ImageNets,… ?
Secondly, if I later would write a converter from one to the other (for comparison), I guess it would be best if I already have the most sophisticated formatting, as downgrading is easier than upgrading the information level.
Could you give me a hint, your opinion, or an overview?
Maybe some other points which could give a clearer picture:
- What is, in your opinion, the best format for hand gesture analysis?
(different gestures, different background). Or more general, which
formats suits which tasks the best? - Can you use the classic train-test split function with the COCO
format? - Does using CSV mean in most cases to put the flattened image into it,
while json the image name? - Which most know, preset network architectures from Github use which
formatting. (For using them as pre-trained networks for transfer
learning)
Thanks a lot
p.s. my answer to you might be delayed, thanks for the patience
neural-network dataset image-classification data-formats
asked Mar 22 at 14:05
Florida ManFlorida Man
61
New contributor
Florida Man is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I have a more general question, which I could not answer after quite a bit of google. Actually, I got more confused. I hope you can share some light.
I am familiar with deep learning, Keras but come from time series analysis and now start in image processing.
Background
What I noticed, that most tutorial use open datasets to explain implementations of CNNs. Each dataset (COCO, ImageNet, CIFAR,…) chooses all different formatting of the annotations and representation of the images.
For example, COCO just e.g. uses the name of the image in json while others use the flattened RGB information of the image in csv.
Now I want to create my own dataset with hand-gestures. Generally, I could just give each image one tag and be finished for image classification. However, I see many implementations of complex Network architectures like RetinaNet, which use formats such as COCOs also for object (here hand) recognition.
The Question(s):
Not knowing if I will later need more sophisticated annotations, should I start with a COCO format? But if so, which should I choose of the many formats? COCOs, ImageNets,… ?
Secondly, if I later would write a converter from one to the other (for comparison), I guess it would be best if I already have the most sophisticated formatting, as downgrading is easier than upgrading the information level.
Could you give me a hint, your opinion, or an overview?
Maybe some other points which could give a clearer picture:
- What is, in your opinion, the best format for hand gesture analysis?
(different gestures, different background). Or more general, which
formats suits which tasks the best? - Can you use the classic train-test split function with the COCO
format? - Does using CSV mean in most cases to put the flattened image into it,
while json the image name? - Which most know, preset network architectures from Github use which
formatting. (For using them as pre-trained networks for transfer
learning)
Thanks a lot
p.s. my answer to you might be delayed, thanks for the patience
neural-network dataset image-classification data-formats
asked Mar 22 at 14:05
Florida ManFlorida Man
61
New contributor
Florida Man is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
I have a more general question, which I could not answer after quite a bit of google. Actually, I got more confused. I hope you can share some light.
I am familiar with deep learning, Keras but come from time series analysis and now start in image processing.
Background
What I noticed, that most tutorial use open datasets to explain implementations of CNNs. Each dataset (COCO, ImageNet, CIFAR,…) chooses all different formatting of the annotations and representation of the images.
For example, COCO just e.g. uses the name of the image in json while others use the flattened RGB information of the image in csv.
Now I want to create my own dataset with hand-gestures. Generally, I could just give each image one tag and be finished for image classification. However, I see many implementations of complex Network architectures like RetinaNet, which use formats such as COCOs also for object (here hand) recognition.
The Question(s):
Not knowing if I will later need more sophisticated annotations, should I start with a COCO format? But if so, which should I choose of the many formats? COCOs, ImageNets,… ?
Secondly, if I later would write a converter from one to the other (for comparison), I guess it would be best if I already have the most sophisticated formatting, as downgrading is easier than upgrading the information level.
Could you give me a hint, your opinion, or an overview?
Maybe some other points which could give a clearer picture:
- What is, in your opinion, the best format for hand gesture analysis?
(different gestures, different background). Or more general, which
formats suits which tasks the best? - Can you use the classic train-test split function with the COCO
format? - Does using CSV mean in most cases to put the flattened image into it,
while json the image name? - Which most know, preset network architectures from Github use which
formatting. (For using them as pre-trained networks for transfer
learning)
Thanks a lot
p.s. my answer to you might be delayed, thanks for the patience
neural-network dataset image-classification data-formats
asked Mar 22 at 14:05
Florida ManFlorida Man
61
New contributor
Florida Man is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I have a more general question, which I could not answer after quite a bit of google. Actually, I got more confused. I hope you can share some light.
I am familiar with deep learning, Keras but come from time series analysis and now start in image processing.
Background
What I noticed, that most tutorial use open datasets to explain implementations of CNNs. Each dataset (COCO, ImageNet, CIFAR,…) chooses all different formatting of the annotations and representation of the images.
For example, COCO just e.g. uses the name of the image in json while others use the flattened RGB information of the image in csv.
Now I want to create my own dataset with hand-gestures. Generally, I could just give each image one tag and be finished for image classification. However, I see many implementations of complex Network architectures like RetinaNet, which use formats such as COCOs also for object (here hand) recognition.
The Question(s):
Not knowing if I will later need more sophisticated annotations, should I start with a COCO format? But if so, which should I choose of the many formats? COCOs, ImageNets,… ?
Secondly, if I later would write a converter from one to the other (for comparison), I guess it would be best if I already have the most sophisticated formatting, as downgrading is easier than upgrading the information level.
Could you give me a hint, your opinion, or an overview?
Maybe some other points which could give a clearer picture:
- What is, in your opinion, the best format for hand gesture analysis?
(different gestures, different background). Or more general, which
formats suits which tasks the best? - Can you use the classic train-test split function with the COCO
format? - Does using CSV mean in most cases to put the flattened image into it,
while json the image name? - Which most know, preset network architectures from Github use which
formatting. (For using them as pre-trained networks for transfer
learning)
Thanks a lot
p.s. my answer to you might be delayed, thanks for the patience
neural-network dataset image-classification data-formats
neural-network dataset image-classification data-formats
asked Mar 22 at 14:05
Florida ManFlorida Man
61
New contributor
Florida Man is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked Mar 22 at 14:05
Florida ManFlorida Man
61
New contributor
Florida Man is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked Mar 22 at 14:05
Florida ManFlorida Man
61
New contributor
Florida Man is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked Mar 22 at 14:05
Florida ManFlorida Man
61
asked Mar 22 at 14:05
Florida ManFlorida Man
61
61
New contributor
Florida Man is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Florida Man is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Florida Man is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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