ImprintX Tactile SDK

High-performance Python SDK for Touch Glove 5-channel tactile data acquisition, RTC time synchronization, real-time 3D displacement/force physical inference (ONNX Runtime / OpenVINO), and H.265 video recording with microsecond-level timestamps.

Powered by a native Rust core with high-efficiency PyO3 bindings.

⚡ Quick Start

Installation

pip install imprintx

High-Level One-Line APIs 🚀

import imprintx

# 1. 实时流式控制台输出
imprintx.stream()

# 2. GUI 网格图形界面展示（支持模型推理与 'b' 键实时去皮标定）
imprintx.show_gui(model="dense_3ch.onnx", device="cuda")

# 3. 抓取并保存 5 通道快照图片
imprintx.save_image(output_dir="./snapshots")

# 4. 录制 H.265 MP4 视频与微秒级时间戳 JSON
imprintx.record_video(output_path="recording.mp4", duration=5.0)

📖 Key Python APIs

1. High-Level Functions

• imprintx.stream(port=None, callback=None, duration=None): Connects to device and streams real-time tactile data to console or custom callback function.

• imprintx.show_gui(port=None, model=None, device="auto"): Opens an OpenCV 2x3 grid window displaying 5-channel real-time tactile images, displacement, and force fields. Press 'q' to exit or 'b' to calibrate zero point.

• imprintx.save_image(port=None, output_dir=".", prefix="tactile", save_grid=True): Captures a 5-channel tactile snapshot and saves channel images (*_ch0.png ... *_ch4.png) and a combined grid image (*_grid.png) to output_dir.

• imprintx.record_video(port=None, output_path="output_h265.mp4", duration=5.0, fps=30.0): Records 5-channel H.265 grid video and exports microsecond-level aligned timestamp JSON metadata.

• imprintx.list_ports(): Scans and returns a list of available serial port paths.

• imprintx.load_video_timestamps(path: str): Loads and parses recorded video timestamp metadata from .json files.

2. Low-Level Core API (TouchGlove Class)

For custom control loops and fine-grained integration:

from imprintx import TouchGlove, list_ports
import time

ports = list_ports()
with TouchGlove(port=ports[0]) as glove:
    print("Device SN:", glove.get_sn())
    glove.sync_rtc()  # Synchronize host clock with hardware RTC
    glove.start()

    while True:
        batch = glove.poll()
        for frame in batch:
            print(f"Ch {frame.channel} | Seq: {frame.seq_id} | Timestamp: {frame.timestamp_us} us | Image: {frame.image.shape}")
        time.sleep(0.01)

TouchGlove Methods

• glove.open(port) / glove.close(): Connection management.
• glove.start() / glove.stop(): Streaming control.
• glove.poll() -> FrameBatch: Fetch latest 5-channel frame batch.
• glove.calibrate_baseline(duration_sec=1.0): Recalibrate zero point.
• glove.get_dense_fields(): Get 5-channel 3D displacement/force fields (5, 32, 32, 3).
• glove.get_sn() / glove.set_sn(sn): Read / write hardware serial number.
• glove.sync_rtc() / glove.query_rtc(): RTC clock synchronization.
• glove.start_recording(output_path) / glove.stop_recording(): Video recording control.

📜 License

Proprietary / All Rights Reserved.