Python matlab_path_editorの例

コード例 #1

ファイル: tester.py プロジェクト: gramuah/ipwt

def test_runner(model, test_set, test_iter, type_):
    matlab_path_editor(type_)


    cmd = os.environ['CAFFE_DIR'] + os.environ['CAFFE_BIN'] + ' test --model=' + os.environ['CONFIG_DIR'] + '/test_' + test_set + '.prototxt' \
    ' --weights=' + model + ' --gpu=' + '0' + ' --iterations=' + '1308' #+ str(test_iter) #1os.environ['DEV_ID']

    print('Running ' + cmd)

    subprocess.call(cmd, shell=True)

コード例 #2

ファイル: crf_runner.py プロジェクト: xiaochengcike/weakly-supervised-segmentation

def grid_search(LOAD_MAT_FILE=1, train2=0):
	# the features  folder save the features computed via the model trained with the train set
	# the features2 folder save the features computed via the model trained with the trainval set

	if train2==1:
		FEATURE_NAME='features2' #features, features2
		TEST_SET = 'test'
	else:
		FEATURE_NAME='features' #features, features2
		TEST_SET = 'val'

	IMG_DIR, CRF_BIN, FEATURE_DIR, SAVE_DIR = grid_setting(FEATURE_NAME, TEST_SET, LOAD_MAT_FILE)
	grid_runner(IMG_DIR, CRF_BIN, FEATURE_DIR, SAVE_DIR)

	os.environ['POSTPROCESS'] = str(1)
	matlab_path_editor(type_)
	matlab_runner()
	matlab_result_runner()

コード例 #3

ファイル: crf_runner.py プロジェクト: 573671712/DeepLab-Context

def grid_search(LOAD_MAT_FILE=1, train2=0):
	# the features  folder save the features computed via the model trained with the train set
	# the features2 folder save the features computed via the model trained with the trainval set

	if train2==1:
		FEATURE_NAME='features2' #features, features2
		TEST_SET = 'test'
	else:
		FEATURE_NAME='features' #features, features2
		TEST_SET = 'val'

	IMG_DIR, CRF_BIN, FEATURE_DIR, SAVE_DIR = grid_setting(FEATURE_NAME, TEST_SET, LOAD_MAT_FILE)
	grid_runner(IMG_DIR, CRF_BIN, FEATURE_DIR, SAVE_DIR)

	os.environ['POSTPROCESS'] = str(1)
	matlab_path_editor(type_)
	matlab_runner()
	matlab_result_runner()

コード例 #4

ファイル: crf_runner.py プロジェクト: yuanzheng625/deepLab-for-video

def crf_runner(LOAD_MAT_FILE=1, train2=0):
    # the features  folder save the features computed via the model trained with the train set
    # the features2 folder save the features computed via the model trained with the trainval set

    if train2 == 1:
        FEATURE_NAME = 'features2'  #features, features2
        TEST_SET = 'test'
        type_ = 2
    else:
        FEATURE_NAME = 'features'  #features, features2
        TEST_SET = 'val'
        type_ = 1

    SAVE_DIR, cmd = dense_setting(FEATURE_NAME, TEST_SET)
    dense_runner(LOAD_MAT_FILE, FEATURE_NAME, TEST_SET, SAVE_DIR, cmd)

    os.environ['POSTPROCESS'] = str(1)
    matlab_path_editor(type_)
    matlab_runner()
    matlab_result_runner()

コード例 #5

ファイル: crf_runner.py プロジェクト: 573671712/DeepLab-Context

def crf_runner(LOAD_MAT_FILE=1, train2=0):
	# the features  folder save the features computed via the model trained with the train set
	# the features2 folder save the features computed via the model trained with the trainval set

	if train2==1:
		FEATURE_NAME='features2' #features, features2
		TEST_SET = 'test'
		type_ = 2
	else:
		FEATURE_NAME='features' #features, features2
		TEST_SET = 'val'
		type_ = 1
		

	SAVE_DIR, cmd = dense_setting(FEATURE_NAME, TEST_SET)
	dense_runner(LOAD_MAT_FILE, FEATURE_NAME, TEST_SET, SAVE_DIR,cmd)

	os.environ['POSTPROCESS'] = str(1)
	matlab_path_editor(type_)
	matlab_runner()
	matlab_result_runner()

コード例 #6

ファイル: tester.py プロジェクト: 573671712/DeepLab-Context

def test_runner(model, test_set, test_iter, type_):
    matlab_path_editor(type_)
    cmd = os.environ['CAFFE_DIR'] + os.environ['CAFFE_BIN'] + ' test --model=' + os.environ['CONFIG_DIR'] + '/test_' + test_set + '.prototxt' \
    ' --weights=' + model + ' --gpu=' + os.environ['DEV_ID'] + ' --iterations=' + str(test_iter)
    print 'Running ' + cmd
    subprocess.call(cmd, shell=True)