Evolution Science

Awesome evo_science created by maycuatroi

Install it from PyPI

pip install evo-science

Example

    model = LinearRegressionModel()

    x = FeatureSet(features=[PClass, Sex, Age, SibSp, Parch, Fare])
    y = FeatureSet(features=[Survived])

    (x + y).build(
        csv_path="https://web.stanford.edu/class/archive/cs/cs109/cs109.1166/stuff/titanic.csv"
    )

    model.fit(x=x, y=y)
    model.evaluate(x=x, y=y, metrics=[Slope, ErrorStd])
    model.calculate_coefficients(x=x)

YOLO Object Detection

The library includes a comprehensive implementation of YOLO (You Only Look Once) object detection models, including YOLOv8. The implementation features:

• Full YOLOv8 architecture with backbone, neck (FPN), and detection head
• Distributed training support
• Real-time object detection with webcam
• Model profiling and EMA (Exponential Moving Average) support
• Custom loss functions including DFL (Distribution Focal Loss)

YOLO Example

from evo_science.packages.yolo.yolo_v8 import YoloV8

# Initialize YOLOv8-nano model
model = YoloV8.yolo_v8_n(num_classes=80)  # 80 classes for COCO dataset

# For training
from evo_science.packages.yolo.modules.trainer import Trainer, TrainerConfig

config = TrainerConfig(
    data_dir="path/to/coco",
    batch_size=32,
    epochs=300,
    input_size=640
)

trainer = Trainer(model, config)
trainer.train()

# For real-time detection using webcam
from evo_science.packages.yolo.modules.demo import demo

demo(input_size=640, model=model)

Development

Read the CONTRIBUTING.md file.