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from dora import DoraStatus |
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import pyarrow as pa |
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import cv2 |
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from idefics2_utils import ask_vlm |
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import pyttsx3 |
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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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engine = pyttsx3.init("espeak") |
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voices = engine.getProperty("voices") |
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engine.setProperty("voice", voices[11].id) |
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def speak(text): |
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engine.say(text) |
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engine.runAndWait() |
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class Operator: |
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def __init__(self): |
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self.instruction = "What is in the image?" |
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self.last_message = "" |
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self.image = None |
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def on_event( |
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self, |
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dora_event, |
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send_output, |
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) -> DoraStatus: |
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if dora_event["type"] == "INPUT": |
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if dora_event["id"] == "image": |
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self.image = ( |
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dora_event["value"] |
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.to_numpy() |
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.reshape((CAMERA_HEIGHT, CAMERA_WIDTH, 3)) |
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) |
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elif dora_event["id"] == "instruction": |
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self.instruction = dora_event["value"][0].as_py() |
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print("instructions: ", self.instruction, flush=True) |
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if self.image is not None: |
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output = ask_vlm(self.image, self.instruction) |
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speak(output) |
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print("response: ", output, flush=True) |
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send_output( |
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"assistant_message", |
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pa.array([output]), |
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dora_event["metadata"], |
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) |
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self.last_message = output |
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return DoraStatus.CONTINUE |
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