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import os |
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from typing import Callable, Optional, Union |
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import cv2 |
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import numpy as np |
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import pyarrow as pa |
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from utils import LABELS |
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from dora import DoraStatus |
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pa.array([]) |
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CI = os.environ.get("CI") |
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CAMERA_WIDTH = 960 |
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CAMERA_HEIGHT = 540 |
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font = cv2.FONT_HERSHEY_SIMPLEX |
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writer = cv2.VideoWriter( |
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"output01.avi", |
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cv2.VideoWriter_fourcc(*"MJPG"), |
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30, |
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(CAMERA_WIDTH, CAMERA_HEIGHT), |
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) |
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class Operator: |
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""" |
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Plot image and bounding box |
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""" |
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def __init__(self): |
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self.image = [] |
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self.bboxs = [] |
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self.bounding_box_messages = 0 |
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self.image_messages = 0 |
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self.text_whisper = "" |
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def on_event( |
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self, |
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dora_event: dict, |
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send_output: Callable[[str, Union[bytes, pa.UInt8Array], Optional[dict]], None], |
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) -> DoraStatus: |
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if dora_event["type"] == "INPUT": |
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return self.on_input(dora_event, send_output) |
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return DoraStatus.CONTINUE |
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def on_input( |
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self, |
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dora_input: dict, |
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send_output: Callable[[str, Union[bytes, pa.UInt8Array], Optional[dict]], None], |
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) -> DoraStatus: |
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""" |
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Put image and bounding box on cv2 window. |
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Args: |
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dora_input["id"] (str): Id of the dora_input declared in the yaml configuration |
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dora_input["value"] (arrow array): message of the dora_input |
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send_output Callable[[str, bytes | pa.UInt8Array, Optional[dict]], None]: |
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Function for sending output to the dataflow: |
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- First argument is the `output_id` |
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- Second argument is the data as either bytes or `pa.UInt8Array` |
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- Third argument is dora metadata dict |
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e.g.: `send_output("bbox", pa.array([100], type=pa.uint8()), dora_event["metadata"])` |
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""" |
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if dora_input["id"] == "image": |
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frame = ( |
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dora_input["value"] |
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.to_numpy() |
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.reshape((CAMERA_HEIGHT, CAMERA_WIDTH, 3)) |
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.copy() |
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) |
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self.image = frame |
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self.image_messages += 1 |
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print("received " + str(self.image_messages) + " images") |
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elif dora_input["id"] == "text" and len(self.image) != 0: |
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self.text_whisper = dora_input["value"][0].as_py() |
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elif dora_input["id"] == "bbox" and len(self.image) != 0: |
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bboxs = dora_input["value"].to_numpy() |
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self.bboxs = np.reshape(bboxs, (-1, 6)) |
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self.bounding_box_messages += 1 |
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print("received " + str(self.bounding_box_messages) + " bounding boxes") |
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for bbox in self.bboxs: |
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[ |
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min_x, |
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min_y, |
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max_x, |
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max_y, |
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confidence, |
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label, |
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] = bbox |
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cv2.rectangle( |
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self.image, |
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(int(min_x), int(min_y)), |
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(int(max_x), int(max_y)), |
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(0, 255, 0), |
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2, |
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) |
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d = ((12 * 22) / (max_y - (CAMERA_HEIGHT / 2))) / 2.77 - 0.08 |
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cv2.putText( |
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self.image, |
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LABELS[int(label)] + f", d={d:.2f}", |
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(int(max_x), int(max_y)), |
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font, |
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0.75, |
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(0, 255, 0), |
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2, |
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1, |
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) |
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cv2.putText( |
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self.image, self.text_whisper, (20, 35), font, 1, (250, 250, 250), 2, 1 |
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) |
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if CI != "true": |
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writer.write(self.image) |
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cv2.imshow("frame", self.image) |
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if cv2.waitKey(1) & 0xFF == ord("q"): |
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return DoraStatus.STOP |
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return DoraStatus.CONTINUE |
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def __del__(self): |
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cv2.destroyAllWindows() |
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