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from Perceptrix.engine import perceptrix, robotix, identify_objects_from_text, search_keyword
from CircumSpect import answer_question, find_object_description, locate_object
from flask import Flask, request, jsonify
import numpy as np
import threading
import whisper
import cv2
import os
model = whisper.load_model("base")
def transcribe(audio):
result = model.transcribe(audio)
transcription = result['text']
print(transcription)
return transcription
app = Flask(__name__)
@app.route('/', methods=['POST', 'GET'])
def home():
return jsonify({'message': 'WORKING'})
def handle_request(func, *args):
try:
result = func(*args)
return jsonify({'message': result})
except Exception as e:
print(e)
return jsonify({'error': str(e)})
@app.route('/locate_object', methods=['POST', 'GET'])
def _locate_object():
image_data = request.json['image']
prompt = request.json['prompt']
image_data = np.array(image_data, dtype=np.uint8)
image = cv2.imdecode(image_data, cv2.IMREAD_COLOR)
cv2.imwrite('API.jpg', image)
return handle_request(locate_object, prompt, "API.jpg")
@app.route('/vqa', methods=['POST', 'GET'])
def _vqa():
image_data = request.json['image']
prompt = request.json['prompt']
image_data = np.array(image_data, dtype=np.uint8)
image = cv2.imdecode(image_data, cv2.IMREAD_COLOR)
cv2.imwrite('API.jpg', image)
return handle_request(answer_question, prompt, "API.jpg")
@app.route('/object_description', methods=['POST', 'GET'])
def _object_description():
image_data = request.json['image']
image_data = np.array(image_data, dtype=np.uint8)
image = cv2.imdecode(image_data, cv2.IMREAD_COLOR)
cv2.imwrite('API.jpg', image)
return handle_request(find_object_description, "API.jpg")
@app.route('/perceptrix', methods=['POST', 'GET'])
def _perceptrix():
prompt = request.json['prompt']
return handle_request(perceptrix, prompt)
@app.route('/robotix', methods=['POST', 'GET'])
def _robotix():
prompt = request.json['prompt']
return handle_request(robotix, prompt)
@app.route('/search_keyword', methods=['POST', 'GET'])
def _search_keyword():
prompt = request.json['prompt']
return handle_request(search_keyword, prompt)
@app.route('/identify_objects_from_text', methods=['POST', 'GET'])
def _identify_objects_from_text():
prompt = request.json['prompt']
return handle_request(identify_objects_from_text, prompt)
@app.route('/transcribe', methods=['POST', 'GET'])
def _upload_audio():
try:
audio_file = request.files['audio']
filename = os.path.join("./", audio_file.filename)
audio_file.save(filename)
print("RECEIVED")
return jsonify({'message': transcribe(filename)})
except Exception as e:
print(e)
return jsonify({'message': "Error"})
def run_app():
app.run(port=7777)
if __name__ == "__main__":
runner = threading.Thread(target=run_app)
runner.start()
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