<commit_before># Cavelab
Deep-vision environment for rapid prototyping and scale deployment. Includes libraries such as Tensorflow and OpenCV. Specifically developed for Peta-scale alignment on EM images, but highly generalizable.

## Usage
```
from cavelab import image_processing, visual

blend_map = image_processing.get_blend_map(256, 512)
visual.save(blend_map, 'blend.jpg')
```

## Build
Build dockerfile and then run the environment
```
./bin/build
./bin/run
```
You would require to have docker. For GPU version Nvidia-Docker (Linux only).

## Manual Setup
Run install (Linux only)
```
./bin/install
```
and import
```
import cavelab
```

## Plans
Minimal Todo

```
V Import all h5 data processings into cavelab
V Import data reading from tfrecords
V Global Sess
V Seperate image processing modules (numpy and tensorflow)
V Import visualization utils
V Import Tensorflow helper layers
V Install OpenCV
V Saving/Loading model
- Import models (Graph Development)
- Rename dual models
- Hyperparameters
- Pair of data samples
- Import Generation of Training data
- Import Inference techniques
- Goal train simple model
```

Scaling Todo
```
- Hyperparameters
- Notion of tasks and sub-tasks
- Experiment tasks
- Async sub-tasking
- Inference tasks
- Task Queue
- Running N instances
- Experiment logging and hypothesis testing
```
<commit_msg>Goals completed including adding Julia<commit_after># Cavelab
Deep-vision environment for rapid prototyping and scale deployment. Includes libraries such as Tensorflow and OpenCV. Specifically developed for Peta-scale alignment on EM images, but highly generalizable.

## Usage
```
from cavelab import image_processing, visual

blend_map = image_processing.get_blend_map(256, 512)
visual.save(blend_map, 'blend.jpg')
```

## Build
Build dockerfile and then run the environment
```
./bin/build
./bin/run
```
You would require to have docker. For GPU version Nvidia-Docker (Linux only).

## Manual Setup
Run install (Linux only)
```
./bin/install
```
and import
```
import cavelab
```

## Plans
Minimal Todo

```
V Import all h5 data processings into cavelab
V Import data reading from tfrecords
V Global Sess
V Seperate image processing modules (numpy and tensorflow)
V Import visualization utils
V Import Tensorflow helper layers
V Install OpenCV
V Saving/Loading model
V Import models (Graph Development)
V Rename dual models
V Goal train simple model
V Pair of data samples
- Hyperparameters
- Import Generation of Training data
- Import Inference techniques

```

Scaling Todo
```
- Hyperparameters
- Notion of tasks and sub-tasks
- Experiment tasks
- Async sub-tasking
- Inference tasks
- Task Queue
- Running N instances
- Experiment logging and hypothesis testing
```

{'fraction_non_alphanumeric': 0.07567964731814843, 'fraction_numerical': 0.005143277002204262, 'mean_word_length': 4.649377593360996, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 2, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '999390', 'n_tokens_mistral': 819, 'n_tokens_neox': 748, 'n_words': 334}