Dumitrana-Mihnea
61 lines
1.6 KiB
Python
61 lines
1.6 KiB
Python
# DEPENDENCIES ------>
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import json
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import pickle
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import numpy as np
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model_dict = pickle.load(open("./model.p", "rb"))
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model = model_dict["model"]
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labels_dict = {1: "hello", 2: "Nothing"}
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hands_data = json.load(open("./data.json", "r"))
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data_aux = []
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# hand landmarks are taken from data.json
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hand = hands_data[0]
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for landmark in hand:
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x = landmark["x"]
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y = landmark["y"]
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z = landmark["z"]
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data_aux.append(x)
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data_aux.append(y)
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data_aux.append(z)
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prediction = model.predict([np.asarray(data_aux)])
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print(prediction)
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predicted_sign = labels_dict[int(prediction[0])]
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print(predicted_sign)
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data_aux = []
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# if results.multi_hand_landmarks:
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# for hand_landmarks in results.multi_hand_landmarks:
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# mp_drawing.draw_landmarks(
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# frame,
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# hand_landmarks,
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# mp_hands.HAND_CONNECTIONS,
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# mp_drawing_styles.get_default_hand_landmarks_style(),
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# mp_drawing_styles.get_default_hand_connections_style())
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#
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# for i in range(len(hand_landmarks.landmark)):
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# x = hand_landmarks.landmark[i].x
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# y = hand_landmarks.landmark[i].y
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# z = hand_landmarks.landmark[i].z
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# data_aux.append(x)
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# data_aux.append(y)
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# data_aux.append(z)
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# x_.append(x)
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# y_.append(y)
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# prediction = model.predict([np.asarray(data_aux)])
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# predicted_sign = labels_dict[int(prediction[0])]
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# data_aux = []
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# x_ = []
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# y_ = []
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#
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# cv2.imshow("Handy", frame)
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# cv2.waitKey(1)
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#
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# capture.release()
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# cv2.destroyAllWindows()
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