semvec/pypi-packages huggingface dataset:
Hipomap 0.1.0
Histopathological image analysis using Grad-CAM representation map
Requires Python: >=3

# HipoMap

![](Capture.PNG)

## Installation
HipoMap support `Python 3`.
It requires `numpy`, `pandas`, `tensorflow`, `scipy`, `scikit-learn`, `seaborn`, `matplotlib`, `openslide-python`, `cv2`.

Quick installation of openslide
1. Update system
```
sudo apt-get update
```
2. install openslide-tools
```
sudo apt-get install openslide-tools
```
3. install openslide
```
pip install openslide
```

```
pip install hipo_map
```

## Documentation

## Quick Start
```python
#Model load
#if you want to loaded keras pre-trained model
from tensorflow.keras.applications.vgg16 import VGG16
model = VGG16()

#if you want to loaded your pre-trained model
from tensorflow.keras.models import load_model 
model = model = load_model(r'./pre_model.h5')

#make representation map
from hipo_map.Hipomap import generateHipoMap
generateHipoMap(inputpath="/home/user/Dataset/", outputpath="/home/user/Rep/", model = model, layer_name="block5_conv3", patch_size=(224, 224))

#draw heatmap
from hipo_map.Hipomap import  draw_represent
draw_represent(path="/home/yeon/Dataset/", K=50, max_value=1000)

#Classify data to cancer/normal with representation map
from hipo_map.hipoClassify import HipoMap
hipomap = HipoMap(K=50)

#1. split data with base(.csv) 
trainset, validset, testset = hipomap.split("./split.csv", dir_normal="/home/user/Dataset/Normal/", dir_cancer="/home/user/Dataset/Cancer")

#2. train the classifier
hipo_model = hipomap.fit(trainset, validset, lr=0.1, epoch=20, batchsize=1, activation_size=196)

#3. get prediction value
prediction = hipomap.predict(test_X=testset[0])

#4. get score (tpr, fpr, auc)
tpr, mean_fpr, auc = hipomap.evaluate_score(label=testset[1])
```
quran.py 0.1
An API wrapper for Quran.com written in Python.
Requires Python: >=3.8

# quran.py
<img src="https://upload.wikimedia.org/wikipedia/commons/a/a5/Blue_Python_3.8_Shield_Badge.svg">
An easy to use API wrapper for Quran.com v4 written in Python.

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install. ([Git](https://git-scm.com/downloads) required as well.)

```bash
pip install git+https://github.com/Jadtz/quran.py.git
```

## Usage

```python
from quran.verses import Verses
vrs = Verses()

vrs.get_chapter() # returns complete chapter from Quran.
vrs.get_juz() # returns all verses from a specific juz(1-30).
vrs.get_page() # returns all verses of a specific Madani Mushaf page(1 to 604).
vrs.get_hizb() # returns all verses from a specific Hizb( half(1-60).
vrs.get_rub() # returns all verses of a specific Rub number(1-240).
vrs.get_verse() # returns a specific ayah with key.
#example for verse key, "10:5" is 5th ayah of 10th surah.
```

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License
[MIT](https://choosealicense.com/licenses/mit/)