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The following minimal example (`main.py`)
```python3
import keras_ocr
pipeline = keras_ocr.pipeline.Pipeline()
image_urls = [
"https://i.imgur.com/euIw5Dt.png",
"https://i.imgur.co…
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following the keras api, let's add a module to fetch datasets for training. we can again use datalad to distribute public datasets for tutorials, tests, and training. i would suggest a separate repo f…
satra updated
4 years ago
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Dear all,
I follow post in "https://blog.keras.io/keras-as-a-simplified-interface-to-tensorflow-tutorial.html"
The little modified code I use is:
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Hello all,
I was wondering if your pruning tools could be used on my object detection models (SSD / Faster RCNN, ...) trained with the tensorflow object detection API.
When training, I don't u…
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I have a Tensorflow 2.x model which is using the TF preprocessing layer (tf.keras.layers.DenseFeatures) and the distributional layer from TF probability (DistributionLambda)
```python
def regres…
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From #13
```
import tensorflow as tf
#import keras.backend as k
#https://github.com/microsoft/tensorflow-directml/issues/352
# https://www.tensorflow.org/guide/distributed_training
#
# https:…
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Hi!
I am developing a clip classificator using features (extracted from a CNN) fed into an LSTM for classification. It's an end-to-end system. I would like to know if it's possible apply eli5 visuali…
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I just write one line:
model.save("./yolov3")
in
for epoch in range(cfg.TRAIN.EPOCHS):
for image_data, target in trainset:
train_step(image_data, target, epoch)
for image_data, …
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