def test_train():
trainset = os.path.join(PROJECT_PATH, _get_random_str())
mod = os.path.join(PROJECT_PATH, "a.h5")
config = {
# fmt: off
"video": {
"path": VIDEO_PATH,
"fps": 30,
},
"output": ".",
"extras": {
"save_train_set": trainset,
}
}
run(config)
# train
keras_train(trainset, model_path=mod, epochs=1)
def test_run_calc():
config = {
# fmt: off
"video": {
"path": VIDEO_PATH,
},
"output": ".",
"calc": {
"output":
f"{_get_random_str()}.json",
"operators": [{
"name": "calc_between_0_1",
"calc_type": "between",
"args": {
"from_stage": "0",
"to_stage": "1",
},
}, {
"name": "display everything",
"calc_type": "display",
}]
}
}
run(config)
def test_run_validation():
# enum
config = {
# fmt: off
"video": {
"path": VIDEO_PATH,
},
"classifier": {
"classifier_type": "unknwonwonn",
},
"output": ".",
}
try:
run(config)
except ValidationError:
pass
else:
raise TypeError(
"should raise an error if classifier_type is unexpected")
config = {
# fmt: off
"video": {
"path": VIDEO_PATH,
},
"output": ".",
"calc": {
"output": f"{_get_random_str()}.json",
"operators": [
{
"name": "error_test",
"calc_type": "unknwonww",
},
]
}
}
try:
run(config)
except ValidationError:
pass
else:
raise TypeError("should raise an error if calc_type is unexpected")
config = {
# fmt: off
"video": {
"path": VIDEO_PATH,
},
"output": ".",
"calc": {
"output":
f"{_get_random_str()}.json",
"ignore_error":
True,
"operators": [
{
"name": "error_test",
"calc_type": "between",
"args": {
"from_stage": "0",
# unexpected stage
"to_stage": "999",
}
},
]
}
}
run(config)