mirror of
https://github.com/azaion/ai-training.git
synced 2026-04-22 06:56:34 +00:00
Alex Bezdieniezhnykh
49 lines
2.2 KiB
Python
49 lines
2.2 KiB
Python
import re
|
|
|
|
import yaml
|
|
import constants
|
|
from azaion_api import Api, ApiCredentials
|
|
from cdn_manager import CDNManager, CDNCredentials
|
|
from inference.inference import Inference
|
|
from inference.onnx_engine import OnnxEngine
|
|
from inference.tensorrt_engine import TensorRTEngine
|
|
from utils import Dotdict
|
|
|
|
if __name__ == "__main__":
|
|
# Inference(OnnxEngine('azaion-2025-03-10.onnx', batch_size=4),
|
|
# confidence_threshold=0.5, iou_threshold=0.3).process('ForAI_test.mp4')
|
|
# detection for the first 200sec of video:
|
|
# onnxInference: 81 sec, 6.3Gb VRAM
|
|
# tensorrt: 54 sec, 3.7Gb VRAM
|
|
|
|
# Inference(TensorRTEngine('azaion-2025-03-10_int8.engine', batch_size=16),
|
|
# confidence_threshold=0.5, iou_threshold=0.3).process('ForAI_test.mp4')
|
|
# INT8 for 200sec: 54 sec 3.7Gb
|
|
|
|
# Inference(TensorRTEngine('azaion-2025-03-10_batch8.engine', batch_size=8),
|
|
# confidence_threshold=0.5, iou_threshold=0.3).process('ForAI_test.mp4')
|
|
|
|
with open(constants.CONFIG_FILE, "r") as f:
|
|
config_dict = yaml.safe_load(f)
|
|
d_config = Dotdict(config_dict)
|
|
cdn_c = Dotdict(d_config.cdn)
|
|
api_c = Dotdict(d_config.api)
|
|
|
|
cdn_manager = CDNManager(CDNCredentials(cdn_c.host,
|
|
cdn_c.downloader_access_key, cdn_c.downloader_access_secret,
|
|
cdn_c.uploader_access_key, cdn_c.uploader_access_secret))
|
|
cdn_manager.download(cdn_c.bucket, constants.AI_TENSOR_MODEL_FILE_BIG)
|
|
cdn_manager.download(cdn_c.bucket, constants.AI_ONNX_MODEL_FILE_BIG)
|
|
|
|
api_client = Api(ApiCredentials(api_c.url, api_c.user, api_c.pw, api_c.folder))
|
|
|
|
tensor_model_bytes = api_client.load_resource(constants.AI_TENSOR_MODEL_FILE_BIG, constants.AI_TENSOR_MODEL_FILE_SMALL)
|
|
onxx_model_bytes = api_client.load_resource(constants.AI_ONNX_MODEL_FILE_BIG, constants.AI_ONNX_MODEL_FILE_SMALL)
|
|
|
|
|
|
# Inference(OnnxEngine(onxx_model_bytes, batch_size=4),
|
|
# confidence_threshold=0.5, iou_threshold=0.3).process('tests/ForAI_test.mp4')
|
|
|
|
Inference(TensorRTEngine(tensor_model_bytes, batch_size=4),
|
|
confidence_threshold=0.5, iou_threshold=0.3).process('tests/ForAI_test.mp4')
|