Note
This is the helper repo for the Indian Bovine Breeds Kaggle dataset.
Minimal Quick Start: Clone, Install, and Run the Keras-Based Identification Script.
git clone https://github.com/pronoym99/Cattle-cloud.git
cd Cattle-cloudpython -m venv .venv
.\.venv\Scripts\Activate.ps1python3 -m venv .venv
source .venv/bin/activatepip install --upgrade pip
pip install tensorflow pillow numpy sqlalchemy# Run from the repository root:
python identification.pyThis will:
- Load the Keras model from models/cattle_identification_keras_model.h5
- Use the sample image at assets/Indian_bovine_breeds/Hallikar/Hallikar_4.jpg
- Print the detected class (e.g.,
Class detected: <BreedName>)
Edit the image path in identification.py:
# In identification.py
from PIL import Image
image = Image.open("path/to/your/image.jpg")Keep the preprocessing (224x224) unchanged.
erDiagram
USER {
int userid PK
int phone
string address
}
LIVESTOCK {
int livestockid PK
string address
}
REGISTRATION {
int regid PK
int userid FK
int livestockid FK
}
TRANSACTIONS {
int txnid PK
string txntime
bool txnstatus
int regid FK
int seller_id FK
int customer_id FK
int livestock_id FK
}
TRANSPORTATION {
int event_id PK
int livestock_id FK
int transporter_user_id FK
string destination_address
string transported_at
}
USER ||--o{ REGISTRATION : "owns"
LIVESTOCK ||--o{ REGISTRATION : "registered via"
REGISTRATION ||--o{ TRANSACTIONS : "referenced in"
USER ||--o{ TRANSACTIONS : "sells"
USER ||--o{ TRANSACTIONS : "buys"
LIVESTOCK ||--o{ TRANSACTIONS : "transferred in"
LIVESTOCK ||--o{ TRANSPORTATION : "transported in"
USER ||--o{ TRANSPORTATION : "transports"