Ankle/yolov5_birdproject
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export.py replace check_file -> check_yaml (#8852)

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* export.py replace `check_file` -> `check_yaml`

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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Glenn Jocherandpre-commit-ci[bot] authored and GitHub committed 2022-08-03 23:38:36 +02:00
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commit 628c05ca6f
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@@ -67,7 +67,7 @@ if platform.system() != 'Windows':
from models.experimental import attempt_load from models.experimental import attempt_load
from models.yolo import Detect from models.yolo import Detect
from utils.dataloaders import LoadImages from utils.dataloaders import LoadImages
from utils.general import (LOGGER, check_dataset, check_file, check_img_size, check_requirements, check_version, from utils.general import (LOGGER, check_dataset, check_img_size, check_requirements, check_version, check_yaml,
colorstr, file_size, print_args, url2file) colorstr, file_size, print_args, url2file)
from utils.torch_utils import select_device from utils.torch_utils import select_device
@@ -371,7 +371,7 @@ def export_tflite(keras_model, im, file, int8, data, nms, agnostic_nms, prefix=c
converter.optimizations = [tf.lite.Optimize.DEFAULT] converter.optimizations = [tf.lite.Optimize.DEFAULT]
if int8: if int8:
from models.tf import representative_dataset_gen from models.tf import representative_dataset_gen
dataset = LoadImages(check_dataset(check_file(data))['train'], img_size=imgsz, auto=False) dataset = LoadImages(check_dataset(check_yaml(data))['train'], img_size=imgsz, auto=False)
converter.representative_dataset = lambda: representative_dataset_gen(dataset, ncalib=100) converter.representative_dataset = lambda: representative_dataset_gen(dataset, ncalib=100)
converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8] converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS_INT8]
converter.target_spec.supported_types = [] converter.target_spec.supported_types = []