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ultralytics 8.0.55 unified YOLOv8 model YAMLs (#1475)

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This commit is contained in:
Glenn Jocher
2023-03-20 13:54:20 +01:00
committed by GitHub
parent 701fba4770
commit 25cc07401f
45 changed files with 203 additions and 896 deletions
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16
ultralytics/yolo/engine/exporter.py
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@ -245,8 +245,7 @@ class Exporter:
if tflite:
f[7], _ = self._export_tflite(s_model, nms=False, agnostic_nms=self.args.agnostic_nms)
if edgetpu:
f[8], _ = self._export_edgetpu(tflite_model=str(
Path(f[5]) / (self.file.stem + '_full_integer_quant.tflite'))) # int8 in/out
f[8], _ = self._export_edgetpu(tflite_model=Path(f[5]) / f'{self.file.stem}_full_integer_quant.tflite')
if tfjs:
f[9], _ = self._export_tfjs()
if paddle: # PaddlePaddle
@ -532,9 +531,16 @@ class Exporter:
subprocess.run(cmd, shell=True)
yaml_save(f / 'metadata.yaml', self.metadata) # add metadata.yaml
# Remove/rename TFLite models
if self.args.int8:
for file in f.rglob('*_dynamic_range_quant.tflite'):
file.rename(file.with_stem(file.stem.replace('_dynamic_range_quant', '_int8')))
for file in f.rglob('*_integer_quant_with_int16_act.tflite'):
file.unlink() # delete extra fp16 activation TFLite files
# Add TFLite metadata
for file in f.rglob('*.tflite'):
self._add_tflite_metadata(file)
f.unlink() if 'quant_with_int16_act.tflite' in str(f) else self._add_tflite_metadata(file)
# Load saved_model
keras_model = tf.saved_model.load(f, tags=None, options=None)
@ -565,9 +571,9 @@ class Exporter:
LOGGER.info(f'\n{prefix} starting export with tensorflow {tf.__version__}...')
saved_model = Path(str(self.file).replace(self.file.suffix, '_saved_model'))
if self.args.int8:
f = saved_model / f'{self.file.stem}_integer_quant.tflite' # fp32 in/out
f = saved_model / f'{self.file.stem}_int8.tflite' # fp32 in/out
elif self.args.half:
f = saved_model / f'{self.file.stem}_float16.tflite'
f = saved_model / f'{self.file.stem}_float16.tflite' # fp32 in/out
else:
f = saved_model / f'{self.file.stem}_float32.tflite'
return str(f), None

6
ultralytics/yolo/engine/model.py
View File

@ -5,7 +5,7 @@ from pathlib import Path
from ultralytics import yolo # noqa
from ultralytics.nn.tasks import (ClassificationModel, DetectionModel, SegmentationModel, attempt_load_one_weight,
guess_model_task, nn)
guess_model_task, nn, yaml_model_load)
from ultralytics.yolo.cfg import get_cfg
from ultralytics.yolo.engine.exporter import Exporter
from ultralytics.yolo.utils import (DEFAULT_CFG, DEFAULT_CFG_DICT, DEFAULT_CFG_KEYS, LOGGER, RANK, ROOT, callbacks,
@ -111,8 +111,8 @@ class YOLO:
task (str) or (None): model task
verbose (bool): display model info on load
"""
self.cfg = check_yaml(cfg) # check YAML
cfg_dict = yaml_load(self.cfg, append_filename=True) # model dict
cfg_dict = yaml_model_load(cfg)
self.cfg = cfg
self.task = task or guess_model_task(cfg_dict)
self.model = TASK_MAP[self.task][0](cfg_dict, verbose=verbose and RANK == -1) # build model
self.overrides['model'] = self.cfg