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config.yaml
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81 lines (67 loc) · 1.96 KB
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dataset_path: "/projects/weilab/dataset/barcode/LZ58_test"
output_path: "outputs"
anisotropy: [40, 16.3, 16.3]
to_um: 0.01
num_cpus: 48
num_gpus: 1
fiber_segmentation_model:
dataset_path: "/projects/weilab/dataset/barcode/train"
fiber_segmentation:
batch_size: 64
_path: fiberpipeline/segmentation/fiber_segmentation_model
checkpoint: ${fiber_segmentation._path}/checkpoints/checkpoint_100000.pth.tar
base_yaml: ${fiber_segmentation._path}/configs/base_config.yaml
bcs_yaml: ${fiber_segmentation._path}/configs/bcs_config.yaml
clahe:
tile_size: 8
clip_limit: 2.0
bcs:
thres1: 0.21290304093127832
thres2: 0.6229526243971144
thres3: 0
thres4: 0
thres5: 0
thres_small: 10
cell_segmentation:
model_type: "vit_b_lm" # base (also t for tiny; l for large), light microscopy
visualize: true
skeletonize_fibers:
manual_z_scale: 0.33
percentile_fit: [0.1, 0.9]
num_centerline_points: 1000
spline_smoothing: null
extrapolate: [-0.2, 1.2]
normalize_signals:
gaussian_filter_ratio: 0.01 # for cropping
midpoint_range: [0.45, 0.55] # for determining midpoint
scale_range: [-0.2, 0.2] # if negative, scale left up, if positive, scale right up
num_trials: 100 # number of bayesian trials to find the best midpoint and scaling
validate_fibers:
thres_length: 800
thres_pca_ratio: 0.0
thres_mean_soma: 0.0
one_per_soma: false
stats:
length_thresh: [800, 2500]
precomputed:
jobs: 64
chunk_size: [16, 64, 64]
downsample_factors:
- [1, 2, 2]
- [2, 2, 2]
- [2, 2, 2]
mesh_mip: 2
mesh_merge_magnitude: 3
im_shader: |
#uicontrol float brightness slider(min=-10, max=10, default=0, step=0.1)
#uicontrol invlerp normalized
#uicontrol vec3 color color
void main() {
float val = normalized();
float alpha = smoothstep(0.0, 1.0, val);
vec3 adjustedColor = color * exp(brightness);
emitRGBA(vec4(adjustedColor, alpha));
}
napari:
# skel_downsample: 10
skel_downsample: 5