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Commit 4b660a76 authored by gospodnetic's avatar gospodnetic
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Split generate stats to smaller functions, introduce a possibility to generate... 

Split generate stats to smaller functions, introduce a possibility to generate a horizontal or vertical stats table (switch models and approaches/methods)
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Benchmark.py
+ 167
− 67
View file @ 4b660a76
......@@ -2,11 +2,18 @@ import utilities as util
from LogContainer import LogContainer
import numpy as np
from enum import Enum
class TableOrientation(Enum):
VERTICAL = 0
HORIZONTAL = 1
class Benchmark:
def __init__(self):
self.log_container_per_model = {}
self.methods_per_approach = {}
self.method_list = set()
self.approach_list = set()
def set_log_containers(self, log_container_per_model):
self.log_container_per_model = log_container_per_model
......@@ -15,99 +22,191 @@ class Benchmark:
def __extract_methods_per_approach(self):
for model in self.log_container_per_model:
for approach in self.log_container_per_model[model].methods_per_approach:
self.approach_list.add(approach)
for method in self.log_container_per_model[model].methods_per_approach[approach]:
self.method_list.add(method)
if approach in self.methods_per_approach:
if method not in self.methods_per_approach[approach]:
self.methods_per_approach[approach].append(method)
else:
self.methods_per_approach[approach] = [method]
def generate_statistic_tex(self, output_path = "./"):
# Generate average discarded values both per approach and per method
def generate_statistic_tex(self, orientation = TableOrientation.VERTICAL, output_path = "./"):
# Per model per method.
filename = output_path + "stats_per_method.tex"
tex_file = open(filename, "w")
filename_per_method = output_path + "stats_per_method.tex"
filename_per_approach = output_path + "stats_per_approach.tex"
if (orientation == TableOrientation.VERTICAL):
self._generate_statistic_per_method_vertical(filename_per_method)
self._generate_statistic_per_approach_vertical(filename_per_approach)
# Per model per approach.
else:
self._generate_statistic_per_method_horizontal(filename_per_method)
self._generate_statistic_per_approach_horizontal(filename_per_approach)
tex_file.write("\n\\begin{table*}\n")
tex_file.write("\\centering\n")
tex_file.write("\\begin{tabular}{|c|")
tex_file.write(" c|" * len(self.log_container_per_model))
tex_file.write("}\n")
tex_file.write("\\hline\n")
def _generate_statistic_per_approach_vertical(self, filename):
tex_file = open(filename, "w")
discarded_per_method = self.get_average_discarded_per_method()
discarded_per_model_per_method = self.get_average_discarded_per_model_per_method()
tex_file.write("\n\\begin{table*}\n")
tex_file.write("\\centering\n")
tex_file.write("\\begin{tabular}{|c|")
tex_file.write(" c|" * len(self.log_container_per_model))
tex_file.write("}\n")
tex_file.write("\\hline\n")
# Write header.
tex_file.write(" ")
for model in self.log_container_per_model:
tex_file.write(" & {}".format(model))
tex_file.write("\\\\\n")
discarded_per_approach = self.get_average_discarded_per_approach()
discarded_per_model_per_approach = self.get_average_discarded_per_model_per_approach()
for method in discarded_per_method:
# Average value over all models.
tex_file.write("\n\\hline\n")
tex_file.write("\\multirow{{{}}}{{*}}{{\\makecell{{{}}}}}".format(2, method))
value = util.set_precision(discarded_per_method[method] * 100, 2)
tex_file.write("\n& \\multicolumn{{4}}{{c|}}{{{}}}".format(value))
# Write header.
tex_file.write(" ")
for model in self.log_container_per_model:
tex_file.write(" & {}".format(model))
tex_file.write("\\\\\n")
# Draw horizontal line spanning only under the multicolumn section.
tex_file.write("\n\\cline{{2-{}}}\n".format(len(self.log_container_per_model) + 1))
# Average value for each model.
for model in discarded_per_model_per_method:
value = util.set_precision(discarded_per_model_per_method[model][method] * 100, 2)
tex_file.write(" & \\makecell{{{}}}".format(value))
for approach in discarded_per_approach:
print(approach)
# Average value over all models.
tex_file.write("\n\\hline\n")
tex_file.write("\\multirow{{{}}}{{*}}{{\\makecell{{{}}}}}".format(2, approach))
value = util.set_precision(discarded_per_approach[approach] * 100, 2)
tex_file.write("\n& \\multicolumn{{4}}{{c|}}{{{}}}".format(value))
tex_file.write("\\\\\n")
# Draw horizontal line spanning only under the multicolumn section.
tex_file.write("\n\\cline{{2-{}}}\n".format(len(self.log_container_per_model) + 1))
# Average value for each model.
for model in discarded_per_model_per_approach:
value = util.set_precision(discarded_per_model_per_approach[model][approach] * 100, 2)
tex_file.write(" & \\makecell{{{}}}".format(value))
tex_file.write("\\\\\n")
tex_file.write("\n\\hline\n")
tex_file.write("\\end{tabular}")
tex_file.write("\n\\end{table*}\n")
tex_file.close()
def _generate_statistic_per_method_vertical(self, filename):
tex_file = open(filename, "w")
tex_file.write("\n\\begin{table*}\n")
tex_file.write("\\centering\n")
tex_file.write("\\begin{tabular}{|c|")
tex_file.write(" c|" * len(self.log_container_per_model))
tex_file.write("}\n")
tex_file.write("\\hline\n")
discarded_per_method = self.get_average_discarded_per_method()
discarded_per_model_per_method = self.get_average_discarded_per_model_per_method()
# Write header.
tex_file.write(" ")
for model in self.log_container_per_model:
tex_file.write(" & {}".format(model))
tex_file.write("\\\\\n")
tex_file.write("\n\\hline\n")
tex_file.write("\\end{tabular}")
tex_file.write("\n\\end{table*}\n")
tex_file.close()
# Per model per approach.
filename = output_path + "stats_per_approach.tex"
tex_file = open(filename, "w")
for method in discarded_per_method:
# Average value over all models.
tex_file.write("\n\\hline\n")
tex_file.write("\\multirow{{{}}}{{*}}{{\\makecell{{{}}}}}".format(2, method))
value = util.set_precision(discarded_per_method[method] * 100, 2)
tex_file.write("\n& \\multicolumn{{{}}}{{c|}}{{{}}}".format(len(self.log_container_per_model), value))
tex_file.write("\\\\\n")
# Draw horizontal line spanning only under the multicolumn section.
tex_file.write("\n\\cline{{2-{}}}\n".format(len(self.log_container_per_model) + 1))
# Average value for each model.
for model in discarded_per_model_per_method:
value = util.set_precision(discarded_per_model_per_method[model][method] * 100, 2)
tex_file.write(" & \\makecell{{{}}}".format(value))
tex_file.write("\\\\\n")
tex_file.write("\n\\hline\n")
tex_file.write("\\end{tabular}")
tex_file.write("\n\\end{table*}\n")
tex_file.close()
def _generate_statistic_per_approach_horizontal(self, filename):
tex_file = open(filename, "w")
tex_file.write("\n\\begin{table*}\n")
tex_file.write("\\centering\n")
tex_file.write("\\begin{tabular}{|c|")
tex_file.write(" c|" * len(self.approach_list))
tex_file.write("}\n")
tex_file.write("\\hline\n")
tex_file.write("\n\\begin{table*}\n")
tex_file.write("\\centering\n")
tex_file.write("\\begin{tabular}{|c|")
tex_file.write(" c|" * len(self.log_container_per_model))
tex_file.write("}\n")
tex_file.write("\\hline\n")
discarded_per_approach = self.get_average_discarded_per_approach()
discarded_per_model_per_approach = self.get_average_discarded_per_model_per_approach()
discarded_per_approach = self.get_average_discarded_per_approach()
discarded_per_model_per_approach = self.get_average_discarded_per_model_per_approach()
# Write header.
tex_file.write(" ")
for approach in discarded_per_approach:
tex_file.write(" & \\rotatebox{{75}}{{{}}}".format(approach))
tex_file.write("\\\\\n")
# Write header.
tex_file.write(" ")
for model in self.log_container_per_model:
tex_file.write(" & {}".format(model))
tex_file.write("\\\\\n")
for model in self.log_container_per_model:
tex_file.write("{}".format(model))
for approach in discarded_per_approach:
value = util.set_precision(discarded_per_model_per_approach[model][approach] * 100, 2)
tex_file.write(" & {}".format(value))
tex_file.write("\\\\\n")
for approach in discarded_per_approach:
print(approach)
# Average value over all models.
tex_file.write("\n\\hline\n")
tex_file.write("\\multirow{{{}}}{{*}}{{\\makecell{{{}}}}}".format(2, approach))
value = util.set_precision(discarded_per_approach[approach] * 100, 2)
tex_file.write("\n& \\multicolumn{{4}}{{c|}}{{{}}}".format(value))
tex_file.write("\\hline\n")
tex_file.write("Average")
for approach in discarded_per_approach:
value = util.set_precision(discarded_per_approach[approach] * 100, 2)
tex_file.write(" & {}".format(value))
tex_file.write("\\\\\n")
# Draw horizontal line spanning only under the multicolumn section.
tex_file.write("\n\\cline{{2-{}}}\n".format(len(self.log_container_per_model) + 1))
# Average value for each model.
for model in discarded_per_model_per_approach:
value = util.set_precision(discarded_per_model_per_approach[model][approach] * 100, 2)
tex_file.write(" & \\makecell{{{}}}".format(value))
tex_file.write("\n\\hline\n")
tex_file.write("\\end{tabular}")
tex_file.write("\n\\end{table*}\n")
tex_file.close()
def _generate_statistic_per_method_horizontal(self, filename):
tex_file = open(filename, "w")
tex_file.write("\n\\begin{table*}\n")
tex_file.write("\\centering\n")
tex_file.write("\\begin{tabular}{|c|")
tex_file.write(" c|" * len(self.method_list))
tex_file.write("}\n")
tex_file.write("\\hline\n")
discarded_per_method = self.get_average_discarded_per_method()
discarded_per_model_per_method = self.get_average_discarded_per_model_per_method()
# Write header.
tex_file.write(" ")
for method in discarded_per_method:
tex_file.write(" & \\rotatebox{{75}}{{{}}}".format(method))
tex_file.write("\\\\\n")
tex_file.write("\n\\hline\n")
tex_file.write("\\end{tabular}")
tex_file.write("\n\\end{table*}\n")
tex_file.close()
for model in self.log_container_per_model:
tex_file.write("{}".format(model))
for method in discarded_per_method:
value = util.set_precision(discarded_per_model_per_method[model][method] * 100, 2)
tex_file.write(" & {}".format(value))
tex_file.write("\\\\\n")
tex_file.write("\\hline\n")
tex_file.write("Average")
for method in discarded_per_method:
value = util.set_precision(discarded_per_method[method] * 100, 2)
tex_file.write(" & {}".format(value))
tex_file.write("\\\\\n")
tex_file.write("\n\\hline\n")
tex_file.write("\\end{tabular}")
tex_file.write("\n\\end{table*}\n")
tex_file.close()
# \usepackage{makecell} needed.
# \usepackage{multirow} needed.
# Generates a table showing how many viewpoint candidates were provided, how many were used after filtering,
# what was the number of optimal viewpoints and the coverage reached.
# If `with_discarded` is set, the table will include the information about how many viewpoints were available
# before and after filtering, otherwise only the total number of used viewpoints will be written.
def generate_performance_tex_table(self, output_path = "./", coverage_threshold=0.99, with_discarded=True):
filename = output_path
if with_discarded:
......@@ -208,6 +307,7 @@ class Benchmark:
tex_file.close()
# \usepackage{longtable} needed.
# Performance of every OVP log file.
def generate_complete_tex_table(self, output_path = "./"):
tex_file = open(output_path + "complete_table.tex", "w")
......
object_space_exploration_per_approach_methods.json
+ 7
− 5
View file @ 4b660a76
{
"SphereSampling": [
"SpaceSampling": [
"AvgBbox",
"MaxBbox",
"MinBbox",
......@@ -10,14 +10,16 @@
"MixedRepositioned",
"MixedRepositionedNormal",
"NoDisplacement"],
"VertexBased": [
"VertexSampling": [
"VertexBBoxCenter",
"VertexNormal"],
"GeometryBased": [
"VertexNormal",
"VertexGronle"],
"PatchSampling": [
"Area",
"ExactCurv",
"ThinPlate",
"NormalDev"]
"NormalDev",
"NoSubdivision"]
}
......
ovp_paths.json
+ 1
− 2
View file @ 4b660a76
[
"/home/pastrva/Projects/VirtualImageProcessing/Fileserver/Papers/2020_Generate_and_Test_Comparison/Results/WithFiltering/gear",
"/home/pastrva/Projects/VirtualImageProcessing/Fileserver/Papers/2020_Generate_and_Test_Comparison/Results/WithFiltering/hirth",
"/home/pastrva/Projects/VirtualImageProcessing/Fileserver/Papers/2020_Generate_and_Test_Comparison/Results/WithFiltering/time_shaft",
"/home/pastrva/Projects/VirtualImageProcessing/Fileserver/Papers/2020_Generate_and_Test_Comparison/Results/WithFiltering/face_shield"
"/home/pastrva/Projects/VirtualImageProcessing/Fileserver/Papers/2020_Generate_and_Test_Comparison/Results/WithFiltering/time_shaft"
]
readme.md
+ 3
− 0
View file @ 4b660a76
#ViewpointOptimizationBenchmark
Example call:
`python3 vob.py object_space_exploration_per_approach_methods.json ovp_paths.json 2020-08-15`
vob.py
+ 4
− 2
View file @ 4b660a76
from Benchmark import Benchmark
from Benchmark import TableOrientation
from Log import Log
from LogContainer import LogContainer
from Vis import Vis
......@@ -88,7 +89,8 @@ def main():
log_container_per_model[model].print_status()
vis.set_logs(log_container_per_model[model])
vis.generate_graphs()
vis.save_graphs(prefix="{}_{}".format(graph_filename_prefix, model), output_path="./data/")
prefix = model if graph_filename_prefix == "" else "{}_{}".format(graph_filename_prefix, model)
vis.save_graphs(prefix=prefix, output_path="./data/")
# vis.show_graphs()
benchmark = Benchmark()
......@@ -96,7 +98,7 @@ def main():
benchmark.generate_performance_tex_table(output_path="./data/", coverage_threshold=0.98, with_discarded=True)
benchmark.generate_performance_tex_table(output_path="./data/", coverage_threshold=0.98, with_discarded=False)
benchmark.generate_complete_tex_table(output_path="./data/")
benchmark.generate_statistic_tex(output_path="./data/")
benchmark.generate_statistic_tex(orientation=TableOrientation.VERTICAL, output_path="./data/")
print("average duration per model", benchmark.get_average_RT_duration_per_model())
benchmark.get_average_discarded_per_model()
......
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