|
- import os
- from enum import Enum
- from typing import Callable
-
- import cv2
- import numpy as np
-
- from utils import LABELS
-
- CI = os.environ.get("CI")
-
- font = cv2.FONT_HERSHEY_SIMPLEX
-
-
- class DoraStatus(Enum):
- CONTINUE = 0
- STOP = 1
-
-
- class Operator:
- """
- Plot image and bounding box
- """
-
- def __init__(self):
- self.image = []
- self.bboxs = []
-
- def on_input(
- self,
- dora_input: dict,
- send_output: Callable[[str, bytes], None],
- ) -> DoraStatus:
- """
- Put image and bounding box on cv2 window.
-
- Args:
- dora_input["id"] (str): Id of the dora_input declared in the yaml configuration
- dora_input["data"] (bytes): Bytes message of the dora_input
- send_output (Callable[[str, bytes]]): Function enabling sending output back to dora.
- """
- if dora_input["id"] == "image":
- frame = np.frombuffer(dora_input["data"], dtype="uint8")
- frame = cv2.imdecode(frame, -1)
- self.image = frame
-
- elif dora_input["id"] == "bbox" and len(self.image) != 0:
- bboxs = np.frombuffer(dora_input["data"], dtype="float32")
- self.bboxs = np.reshape(bboxs, (-1, 6))
- for bbox in self.bboxs:
- [
- min_x,
- min_y,
- max_x,
- max_y,
- confidence,
- label,
- ] = bbox
- cv2.rectangle(
- self.image,
- (int(min_x), int(min_y)),
- (int(max_x), int(max_y)),
- (0, 255, 0),
- 2,
- )
-
- cv2.putText(
- self.image,
- LABELS[int(label)] + f", {confidence:0.2f}",
- (int(max_x), int(max_y)),
- font,
- 0.75,
- (0, 255, 0),
- 2,
- 1,
- )
-
- if CI != "true":
- cv2.imshow("frame", self.image)
- if cv2.waitKey(1) & 0xFF == ord("q"):
- return DoraStatus.STOP
-
- return DoraStatus.CONTINUE
-
- def __del__(self):
- cv2.destroyAllWindows()
|