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Add instruction to install from the source #73

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55356cd
Update cell_nucleus_segmentor.py
watarungurunnn Jul 25, 2022
4d13918
update README
watarungurunnn Aug 16, 2022
fb02701
Merge remote-tracking branch 'upstream/master'
watarungurunnn Aug 16, 2022
e1cdd48
Update README.md
watarungurunnn Aug 23, 2022
6e30efd
Merge branch 'master' into wataru/instruction
devoworm Mar 8, 2024
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17 changes: 11 additions & 6 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -26,16 +26,19 @@
### Installation
```python
pip install devolearn

# or you can build from the source:
pip install git+https://github.com/DevoLearn/devolearn
```
### Example notebooks
<p align="center">
<img src = "https://raw.githubusercontent.com/DevoLearn/data-science-demos/master/Networks/nodes_matrix_long_smooth.gif" width = "40%">
<img src = "https://raw.githubusercontent.com/DevoLearn/data-science-demos/master/Networks/3d_node_map.gif" width = "40%">
<img src = "https://raw.githubusercontent.com/DevoLearn/data-science-demos/master/Networks/3d_node_map.gif" width = "40%">
</p>

* [Extracting centroid maps and making 3d centroid models](https://nbviewer.jupyter.org/github/DevoLearn/data-science-demos/blob/master/Networks/experiments_with_devolearn_node_maps.ipynb)

### Segmenting the Cell Membrane in C. elegans embryo
### Segmenting the Cell Membrane in C. elegans embryo
<p align="center">
<img src = "https://raw.githubusercontent.com/DevoLearn/devolearn/master/images/pred_centroids.gif" width = "80%">
</p>
Expand All @@ -54,7 +57,7 @@ plt.imshow(seg_pred)
plt.show()
```

* Running the model on a video and saving the predictions into a folder
* Running the model on a video and saving the predictions into a folder
```python
filenames = segmentor.predict_from_video(video_path = "sample_data/videos/seg_sample.mov", centroid_mode = False, save_folder = "preds")
```
Expand All @@ -73,7 +76,7 @@ df = segmentor.predict_from_video(video_path = "sample_data/videos/seg_sample.mo
df.to_csv("centroids.csv")
```

### Segmenting the Cell Nucleus in C. elegans embryo
### Segmenting the Cell Nucleus in C. elegans embryo
<p align="center">
<img src = "https://github.com/Mainakdeb/devolearn/blob/master/images/nucleus_segmentation.gif" width = "60%">
</p>
Expand Down Expand Up @@ -106,7 +109,7 @@ generator = embryo_generator_model()

* Generating a picture and viewing it with [matplotlib](https://matplotlib.org/)
```python
gen_image = generator.generate()
gen_image = generator.generate()
plt.imshow(gen_image)
plt.show()

Expand All @@ -126,7 +129,7 @@ generator.generate_n_images(n = 5, foldername= "generated_images", image_size= (
<img src = "https://raw.githubusercontent.com/devoworm/GSoC-2020/master/Pre-trained%20Models%20(DevLearning)/images/resnet_preds_with_input.gif" width = "60%">
</p>

* Importing the population model for inferences
* Importing the population model for inferences
```python
from devolearn import lineage_population_model
```
Expand Down Expand Up @@ -156,6 +159,8 @@ plot.show()
| **Model** | **Data source** |
|-------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Segmenting the cell membrane in C. elegans embryo | [3DMMS: robust 3D Membrane Morphological Segmentation of C. elegans embryo](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-019-2720-x#Abs1/) |
| Segmenting the nucleus in C. elegans embryo | [C. elegans Cell-Tracking-Challenge dataset](http://celltrackingchallenge.net/3d-datasets/)
| Cell lineage population prediction + embryo GAN | [EPIC dataset](https://epic.gs.washington.edu/)
| Segmenting the nucleus in C. elegans embryo | [C. elegans Cell-Tracking-Challenge dataset](http://celltrackingchallenge.net/3d-datasets/)
| Cell lineage population prediction + embryo GAN | [EPIC dataset](https://epic.gs.washington.edu/)

Expand Down
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