semvec/pypi-packages huggingface dataset:
deadlift 0.1.1
A personal ML model toolkit. Plug-and-play inference for various deep learning models.
License: Apache-2.0
Requires Python: >=3.10
Keywords: deep-learning, segmentation, crack-detection, inspection, nnunet

# deadlift

A personal ML model toolkit. Plug-and-play inference for various deep learning models.

## Installation

```bash
pip install deadlift
```

Model weights are downloaded automatically from HuggingFace on first use.

## Crack Detection

```python
from deadlift.crack import CrackModel

model = CrackModel(device="auto")
result = model.predict("image.jpg")

# result["crack_mask"]   — binary mask (numpy array)
# result["crack_prob"]   — probability heatmap (numpy array)
# result["detections"]   — list of filtered detections with bboxes
# result["overlay"]      — annotated image with bounding boxes
```

### Configuration

```python
# Fast mode
model = CrackModel(device="mps", mirroring=False, tile_step=0.75)

# Max accuracy
model = CrackModel(device="cuda", mirroring=True, tile_step=0.5)

# Custom confidence threshold
result = model.predict("image.jpg", min_confidence=0.5, min_area=200)
```

### Save outputs

```python
import cv2

result = model.predict("image.jpg")
cv2.imwrite("overlay.png", result["overlay"])
cv2.imwrite("mask.png", result["crack_mask"])
```
rhylthyme-mcp 0.1.0
MCP server for creating interactive schedule visualizations with Claude
License: Apache-2.0
Requires Python: >=3.10

# rhylthyme-mcp

MCP server that lets Claude create interactive schedule visualizations from natural language.

## Install

```bash
pip install rhylthyme-mcp
```

## Setup

Add to your Claude Desktop config (`~/Library/Application Support/Claude/claude_desktop_config.json` on Mac):

```json
{
  "mcpServers": {
    "rhylthyme": {
      "command": "rhylthyme-mcp"
    }
  }
}
```

Restart Claude Desktop.

## Usage

Ask Claude to plan or schedule anything:

- "Plan a Thanksgiving dinner for 12 people"
- "Schedule an RNA extraction protocol"
- "Coordinate a bakery production run for tomorrow morning"
- "Make a schedule for cooking beef stew and a side salad"

Claude will generate a structured schedule and open an interactive timeline in your browser with playback controls, track visualization, and an itinerary view.

## How it works

1. You describe a process in natural language
2. Claude generates a Rhylthyme program JSON (parallel tracks, durations, dependencies, resource constraints)
3. The MCP server sends it to rhylthyme.com for rendering
4. An interactive HTML timeline opens in your browser
5. Program JSON is saved to `~/.rhylthyme/visualizations/`

## Requirements

- Python 3.10+
- Claude Desktop with MCP support