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config.yaml
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config.yaml
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%YAML:1.2
---
##########################################
# THIS IS THE YACCLAB CONFIGURATION FILE #
##########################################
# -------------------- #
# Benchmark Tests #
# -------------------- #
CPU 2D 8-way connectivity:
execute: false
# Tests to perform and their number of repetitions
# ------------------------------------------------
perform:
correctness: true
average: true
average_with_steps: false
density: false
granularity: true
memory: false
correctness_tests:
eight_connectivity_standard: true
eight_connectivity_steps: true
eight_connectivity_memory: false
tests_number:
average: 10
average_with_steps: 10
density: 10
granularity: 10
# List of 2D CPU CCL algorithms to test
# -------------------------------------
algorithms:
# - SAUF_RemSP
# - SAUF_TTA
- SAUF_UFPC
# - SAUF_UF
# - BBDT_RemSP
# - BBDT_TTA
- BBDT_UFPC
# - BBDT_UF
# - CCIT_RemSP
# - CCIT_TTA
# - CCIT_UFPC
# - CCIT_UF
# - CTB_RemSP
# - CTB_TTA
# - CTB_UFPC
# - CTB_UF
# - PRED_RemSP
# - PRED_TTA
- PRED_UFPC
# - PRED_UF
# - DRAG_RemSP
# - DRAG_TTA
- DRAG_UFPC
# - DRAG_UF
# - Spaghetti_RemSP
# - Spaghetti_TTA
- Spaghetti_UFPC
# - Spaghetti_UF
# - LSL_STD_TTA
# - LSL_STD_UF
# - LSL_STDZ_TTA
# - LSL_STDZ_UF
# - LSL_RLE_TTA
# - LSL_RLE_UF
# - LSL_RLEZ_TTA
# - LSL_RLEZ_UF
# - DiStefano
# - CT
# - SBLA
# - labeling_NULL
# Algorithms which require to specify a labels solver are: SAUF, BBDT, CCIT, LSL, CTB, PRED, DRAG and Spaghetti
# Possible labels solvers are: UF, UFPC, RemSP, TTA
# LSL requires also a version specifier: STD, STDZ, RLE, RLEZ; only UF and TTA solvers can be used with LSL
# Algorithms which don't require to specify a labels solver are: DiStefano, CT, SBLA, NULL
# Datasets to use for each test
# -----------------------------
# Note that perform correctness tests on labeling_NULL algorithm does not make sense
check_datasets: ["check", "3dpes", "fingerprints", "hamlet", "medical", "mirflickr", "tobacco800", "xdocs"]
# List of datasets on which "Average Runtime Tests" shall be run
average_datasets: ["3dpes", "fingerprints", "hamlet", "medical", "mirflickr", "tobacco800", "xdocs"]
# List of datasets on which "Average Runtime Tests With Steps" shall be run
average_datasets_with_steps: ["3dpes", "fingerprints", "hamlet", "medical", "mirflickr", "tobacco800", "xdocs"]
# List of datasets on which "Memory Tests" shall be run
memory_datasets: ["3dpes", "fingerprints", "hamlet", "medical", "mirflickr", "tobacco800", "xdocs"]
# Save the results of each run test
save_middle_tests: {average: false, average_with_steps: false, density: false, granularity: false}
GPU 2D 8-way connectivity:
execute: true
# Tests to perform and their number of repetitions
# -------------------------------------------------
perform:
correctness: true
average: false
average_with_steps: false
density: false
granularity: false
memory: false
blocksize: false
correctness_tests:
eight_connectivity_standard: true
eight_connectivity_steps: true
eight_connectivity_memory: false
eight_connectivity_blocksize: false
tests_number:
average: 10
average_with_steps: 10
density: 10
granularity: 10
blocksize: 10
# List of 2D GPU CCL algorithms to test
# -------------------------------------
algorithms:
# - BUF
# - BKE
# - BE
# - UF
# - OLE
# - LBUF
# - KE
# - DLP
- BRB
# Datasets to use for each test
# -----------------------------
# Note that perform correctness tests on labeling_NULL algorithm does not make sense
#check_datasets: ["check", "3dpes", "fingerprints", "hamlet", "medical", "mirflickr", "tobacco800", "xdocs"]
check_datasets: ["fingerprints", "hamlet"]
# List of datasets on which "Average Runtime Tests" shall be run
average_datasets: ["3dpes", "fingerprints", "hamlet", "medical", "mirflickr", "tobacco800", "xdocs"]
# List of datasets on which "Average Runtime Tests With Steps" shall be run
average_datasets_with_steps: ["3dpes", "fingerprints", "hamlet", "medical", "mirflickr", "tobacco800", "xdocs"]
# List of datasets on which "Memory Tests" shall be run
memory_datasets: ["3dpes", "fingerprints", "hamlet", "medical", "mirflickr", "tobacco800", "xdocs"]
# List of datasets on which "Blocksize Tests" shall be run
blocksize_datasets: ["3dpes", "fingerprints", "hamlet", "medical", "mirflickr", "tobacco800", "xdocs"]
blocksize:
x: [2, 64, 2]
y: [2, 64, 2]
z: [1, 1, 1]
# Save the results of each run test
save_middle_tests: {average: false, average_with_steps: false, density: false, granularity: false}
# -------------------- #
# Additional utilities #
# -------------------- #
# Directory for input/output paths
paths: {input: "F:/lavoro/dataset/YACCLAB", output: "F:/lavoro/progetti/survey_ccl_gpu/YACCLAB/MSVC2019_CUDA_x64/output"}
# Save the returned number of components in output files
write_n_labels: false
# Save labeled image (TODO: remove this option from tests and add a specific tools for doing that in YACCLAB)
color_labels: {average: false, density: false} #TODO
os: "Windows 10.0.19041"
##########################################
# This is the YACCLAB configuration file #
##########################################