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# Copyright (C) 2024 Intel Corporation
# SPDX-License-Identifier: Apache-2.0
#
"""Async executor based on ModelAPI."""
from __future__ import annotations
import time
from typing import TYPE_CHECKING, Any
from model_api.pipelines import AsyncPipeline
if TYPE_CHECKING:
import numpy as np
from demo_package.model_wrapper import ModelWrapper
from demo_package.streamer import get_streamer
from demo_package.visualizers import BaseVisualizer, dump_frames
class AsyncExecutor:
"""Async inferencer.
Args:
model: model for inference
visualizer: visualizer of inference results
"""
def __init__(self, model: ModelWrapper, visualizer: BaseVisualizer) -> None:
self.model = model
self.visualizer = visualizer
self.async_pipeline = AsyncPipeline(self.model.core_model)
def run(self, input_stream: int | str, loop: bool = False) -> None:
"""Async inference for input stream (image, video stream, camera)."""
streamer = get_streamer(input_stream, loop)
next_frame_id = 0
next_frame_id_to_show = 0
stop_visualization = False
saved_frames = []
for frame in streamer:
results = self.async_pipeline.get_result(next_frame_id_to_show)
while results:
start_time = time.perf_counter()
output = self.render_result(results)
next_frame_id_to_show += 1
self.visualizer.show(output)
if self.visualizer.output:
saved_frames.append(output)
stop_visualization = self.visualizer.is_quit()
# visualize video not faster than the original FPS
self.visualizer.video_delay(time.perf_counter() - start_time, streamer)
results = self.async_pipeline.get_result(next_frame_id_to_show)
if stop_visualization:
break
self.async_pipeline.submit_data(frame, next_frame_id, {"frame": frame})
next_frame_id += 1
self.async_pipeline.await_all()
for next_id in range(next_frame_id_to_show, next_frame_id):
start_time = time.perf_counter()
results = self.async_pipeline.get_result(next_id)
if not results:
msg = "Async pipeline returned None results"
raise RuntimeError(msg)
output = self.render_result(results)
self.visualizer.show(output)
if self.visualizer.output:
saved_frames.append(output)
# visualize video not faster than the original FPS
self.visualizer.video_delay(time.perf_counter() - start_time, streamer)
dump_frames(saved_frames, self.visualizer.output, input_stream, streamer)
def render_result(self, results: tuple[Any, dict]) -> np.ndarray:
"""Render for results of inference."""
predictions, frame_meta = results
current_frame = frame_meta["frame"]
return self.visualizer.draw(current_frame, predictions)
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