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executor_test2.py
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executor_test2.py
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"""
Created on 25/09/21 10:19 AM
@author: Kartik Prabhu
"""
import Baseconfig
from PipelineManager import PipelineManager
from ModelManager import ModelType
if __name__ == '__main__':
config = Baseconfig.config
config.load_model = True
# model_names = ["test_86","test_123","test_126","test_111","test_124","test_127","test_123_1","test_126_1","test_124_1","test_127_1"]
# model_types = [ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,ModelType.PIX2VOXEL,ModelType.PIX2VOXEL,ModelType.PIX2VOXEL,ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,ModelType.PIX2VOXEL,ModelType.PIX2VOXEL]
# chair_dataset = 10*[False]
# thresholds = [0.05,0.05,0.05,0.07,0.05,0.10,0.07,0.05,0.10,0.05]
#
# model_names = model_names+["test_68_2","test_71_2","test_130","test_136",
# "test_112","test_114","test_90","test_89","test_95","test_97","test_109",
# "test_113","test_115","test_92","test_93","test_96","test_98","test_110",
# "test_122","test_118","test_107","test_105","test_116",
# "test_125","test_119","test_108","test_106","test_117"]
# model_types = model_types+[ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,ModelType.PIX2VOXEL,ModelType.PIX2VOXEL,
# ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,
# ModelType.PIX2VOXEL,ModelType.PIX2VOXEL,ModelType.PIX2VOXEL,ModelType.PIX2VOXEL,ModelType.PIX2VOXEL,ModelType.PIX2VOXEL,ModelType.PIX2VOXEL,
# ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP,
# ModelType.PIX2VOXEL,ModelType.PIX2VOXEL,ModelType.PIX2VOXEL,ModelType.PIX2VOXEL,ModelType.PIX2VOXEL]
# chair_dataset = chair_dataset+4*[False]+24*[True]
# # [0.05, 0.075, .1, .2, .3, .4, .5, .6, .7]
# thresholds = thresholds+[0.10,0.05,0.2,0.05,
# .3,.07,.1,.2,.3,.5,.3,
# .07,.1,.05,.5,.05,.5,.05,
# .2,.2,.2,.3,.4,
# .05,.1,0.05,.07,.1]
# model_names = ["test_135","test_114","test_115"]
# model_types = [ModelType.PIX2VOXEL,ModelType.PIX2VOXELPP,ModelType.PIX2VOXELPP]
# chair_dataset = [False]+2*[True]
# thresholds = [0.1,0.07,0.2]
# model_names = ["test_114","test_144","test_145","test_146","test_147"]
# model_types = [ModelType.PIX2VOXEL,ModelType.PIX2VOXELPP,ModelType.PIX2VOXEL,ModelType.PIX2VOXELPP,ModelType.PIX2VOXEL]
# chair_dataset = [True]+ 4*[False]
# thresholds = [0.07,0.05,0.05,0.05,0.05]
model_names = ["test_148","test_149","test_150","test_151"]
model_types = [ModelType.PIX2VOXELPP,ModelType.PIX2VOXEL,ModelType.PIX2VOXELPP,ModelType.PIX2VOXEL]
chair_dataset = 4*[True]
thresholds = [0.3,0.05,0.2,0.1]
for model_name, model_type, chair, thresh in zip(model_names,model_types,chair_dataset, thresholds):
try:
print("Testing for model name:" +model_name+" model type:"+model_type)
config.pretrained_name = model_name
config.main_name = model_name+"_testing_best"
config.model_type = model_type
config.save_count = 70
config.tensorboard_train = config.output_path + config.main_name + '/tensorboard/tensorboard_training/'
config.tensorboard_validation = config.output_path + config.main_name + '/tensorboard/tensorboard_validation/'
config.checkpoint_path = config.output_path + config.main_name + "/"
config.pretrained_checkpoint_path = config.output_path + config.pretrained_name + "/"
config.pix3d.test_indices = config.root_path+'/Datasets/pix3d/splits/pix3d_test_chair.npy' if chair else config.root_path+'/Datasets/pix3d/splits/pix3d_test_2.npy'
print("configuration: " + str(config))
config.TEST.VOXEL_THRESH_IMAGE = thresh
pipeline = PipelineManager(config).get_pipeline(pipeline_type=config.pipeline_type)
# pipeline.save_test_Images()
pipeline.empty_test()
pipeline = None
except Exception as ex:
print("Exception!!!!!!!!!!!!!!!!!!!")
print(ex)