Chiebot-Mirror
/
ultralytics
9
0
Fork 1
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Constrain OpenVINO versions to `>=2024.0.0,<2025.0.0` (#19122)

Browse Source 
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Laughing <61612323+Laughing-q@users.noreply.github.com>
pull/19376/head^2
Francesco Mattioli 2 weeks ago committed by GitHub
parent 941c1743e6
commit 27f004a179
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
3 changed files with 5 additions and 5 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Unified View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 2
      pyproject.toml
  2. 4
      ultralytics/engine/exporter.py
  3. 4
      ultralytics/nn/autobackend.py

2
pyproject.toml
Unescape View File

@ -97,7 +97,7 @@ export = [
"onnx>=1.12.0", # ONNX export "onnx>=1.12.0", # ONNX export
"coremltools>=7.0; platform_system != 'Windows' and python_version <= '3.11'", # CoreML supported on macOS and Linux "coremltools>=7.0; platform_system != 'Windows' and python_version <= '3.11'", # CoreML supported on macOS and Linux
"scikit-learn>=1.3.2; platform_system != 'Windows' and python_version <= '3.11'", # CoreML k-means quantization "scikit-learn>=1.3.2; platform_system != 'Windows' and python_version <= '3.11'", # CoreML k-means quantization
"openvino>=2024.0.0", # OpenVINO export "openvino>=2024.0.0,<2025.0.0", # OpenVINO export
"tensorflow>=2.0.0", # TF bug https://github.com/ultralytics/ultralytics/issues/5161 "tensorflow>=2.0.0", # TF bug https://github.com/ultralytics/ultralytics/issues/5161
"tensorflowjs>=3.9.0", # TF.js export, automatically installs tensorflow "tensorflowjs>=3.9.0", # TF.js export, automatically installs tensorflow
"tensorstore>=0.1.63; platform_machine == 'aarch64' and python_version >= '3.9'", # for TF Raspberry Pi exports "tensorstore>=0.1.63; platform_machine == 'aarch64' and python_version >= '3.9'", # for TF Raspberry Pi exports

4
ultralytics/engine/exporter.py
Unescape View File

@ -570,7 +570,7 @@ class Exporter:
@try_export @try_export
def export_openvino(self, prefix=colorstr("OpenVINO:")): def export_openvino(self, prefix=colorstr("OpenVINO:")):
"""YOLO OpenVINO export.""" """YOLO OpenVINO export."""
check_requirements("openvino>=2024.5.0") check_requirements("openvino>=2024.0.0,<2025.0.0")
import openvino as ov import openvino as ov
LOGGER.info(f"\n{prefix} starting export with openvino {ov.__version__}...") LOGGER.info(f"\n{prefix} starting export with openvino {ov.__version__}...")
@ -592,7 +592,7 @@ class Exporter:
if self.model.task != "classify": if self.model.task != "classify":
ov_model.set_rt_info("fit_to_window_letterbox", ["model_info", "resize_type"]) ov_model.set_rt_info("fit_to_window_letterbox", ["model_info", "resize_type"])
ov.runtime.save_model(ov_model, file, compress_to_fp16=self.args.half) ov.save_model(ov_model, file, compress_to_fp16=self.args.half)
yaml_save(Path(file).parent / "metadata.yaml", self.metadata) # add metadata.yaml yaml_save(Path(file).parent / "metadata.yaml", self.metadata) # add metadata.yaml
if self.args.int8: if self.args.int8:

4
ultralytics/nn/autobackend.py
Unescape View File

@ -244,7 +244,7 @@ class AutoBackend(nn.Module):
# OpenVINO # OpenVINO
elif xml: elif xml:
LOGGER.info(f"Loading {w} for OpenVINO inference...") LOGGER.info(f"Loading {w} for OpenVINO inference...")
check_requirements("openvino>=2024.0.0") check_requirements("openvino>=2024.0.0,<2025.0.0")
import openvino as ov import openvino as ov
core = ov.Core() core = ov.Core()
@ -600,7 +600,7 @@ class AutoBackend(nn.Module):
results[userdata] = request.results results[userdata] = request.results
# Create AsyncInferQueue, set the callback and start asynchronous inference for each input image # Create AsyncInferQueue, set the callback and start asynchronous inference for each input image
async_queue = self.ov.runtime.AsyncInferQueue(self.ov_compiled_model) async_queue = self.ov.AsyncInferQueue(self.ov_compiled_model)
async_queue.set_callback(callback) async_queue.set_callback(callback)
for i in range(n): for i in range(n):
# Start async inference with userdata=i to specify the position in results list # Start async inference with userdata=i to specify the position in results list

Write Preview
Loading…
Cancel
Save