Tutorial 2: Peak Detection

Peak detection relies on mlgidDETECT package. First, create the mlgidBASE class instance:

from mlgidbase import mlgidBASE
filename = '../../example/BA2PbI4.h5'
analysis = mlgidBASE(filename=filename)

INFO - Failed to extract font properties from /usr/share/fonts/truetype/noto/NotoColorEmoji.ttf: Can not load face (unknown file format; error code 0x2)

INFO - generated new fontManager

2026-05-26 14:09:55.283824876 [W:onnxruntime:Default, device_discovery.cc:283 GetGpuDevices] Failed to detect devices under "/sys/class/drm/card0": device_discovery.cc:93 ReadFileContents Failed to open file: "/sys/class/drm/card0/device/vendor"

Then run detection:

Minimal Code Example

analysis.run_detection()

INFO - Model file does not exist.

INFO - Starting download of model file to /home/docs/.local/share/mlgiddetect/dino.onnx

  [######--------------------------------------------]  12.2%  118.5/968.4 MB  236.94 MB/s   

  [#############-------------------------------------]  27.2%  263.9/968.4 MB  290.64 MB/s   

  [####################------------------------------]  41.4%  400.5/968.4 MB  273.30 MB/s   

  [#############################---------------------]  58.4%  565.6/968.4 MB  330.23 MB/s   

  [####################################--------------]  72.6%  702.7/968.4 MB  274.07 MB/s   

  [########################################----------]  80.3%  777.2/968.4 MB  136.48 MB/s   

  [###############################################---]  94.1%  911.3/968.4 MB  263.56 MB/s   

  [##################################################] 100.0%  968.4/968.4 MB  252.97 MB/s   

INFO - Model file downloaded successfully from https://huggingface.co/mlgid-project/mlgidDETECTdino/resolve/main/model.onnx?download=true to /home/docs/.local/share/mlgiddetect/dino.onnx

INFO - Loading model

INFO - Saved detected peaks to file: ../../example/BA2PbI4.h5, entry: entry_0000, frame: 0

Parameters

entry (str) — Data file entry to process. Defaults to None (all entries). OPTIONAL
frame_num (int/List[int]) — Frame number in each entry for detection / list of frames. Defaults to None (all frames).
config_file (str) — Path to detection configuration file. Defaults to None (default parameters). OPTIONAL
model_type (str) — Name of the model dino or faster_rcnn. OPTIONAL

Decription

The user can specify a single entry or process all entries in the file by setting entry=None. The frame_num parameter accepts either a single int or a list of frame indices to process.

The detection configuration can be loaded from a YAML file. Additionally, the detection model can be selected via the model_type parameter. Currently, two models are supported: dino and faster_rcnn, as described in the recent work by C. Völter.

Informational logs indicate whether the detection model is being loaded. After the initial load, both the model and its configuration remain fixed; any subsequent configuration inputs will be ignored. To apply a different configuration, a new mlgidBASE instance must be created with the desired settings.

analysis = mlgidBASE(filename=filename)
analysis.run_detection(
    entry='entry_0000',
    frame_num=0,
    config_detect='../../example/config.yaml',
    model_type = 'faster_rcnn')

ERROR - Configuration file not found: ../../example/config.yaml

An exception has occurred, use %tb to see the full traceback.

SystemExit

/home/docs/checkouts/readthedocs.org/user_builds/mlgidbase/envs/stable/lib/python3.11/site-packages/IPython/core/interactiveshell.py:3756: UserWarning: To exit: use 'exit', 'quit', or Ctrl-D.
  warn("To exit: use 'exit', 'quit', or Ctrl-D.", stacklevel=1)

The results can be visualized using silx view or loaded from the saved file, as shown in Tutorial 8.