41 lines
1.2 KiB
Python
41 lines
1.2 KiB
Python
import streamlit as st
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from process_video import segment_video, classify
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from io import StringIO
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import cv2 as cv
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import tempfile
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import numpy as np
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import tensorflow as tf
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from crop_hand_skeleton import crop_hand
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from cvzone.HandTrackingModule import HandDetector
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if __name__ == "__main__":
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detector = HandDetector(maxHands=1, mode=True, detectionCon=0.7, minTrackCon=0.8)
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model = tf.keras.models.load_model('model_pred/VGG16_sign_char_detection_model')
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st.set_page_config(
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page_title="Projekt widzenie"
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)
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st.title("Projekt rozpoznawanie liter z alfabetu znaków migowych z wideo")
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st.write('Załaduj film')
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upload_movie = st.file_uploader("Wybierz film", type=["mp4"])
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if upload_movie:
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st.write("Film się ładuje.....")
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tfile = tempfile.NamedTemporaryFile(delete=False)
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tfile.write(upload_movie.read())
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video_cap = cv.VideoCapture(tfile.name)
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result, num = segment_video(video_cap, fps=10)
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st.write(f"Załadowano {num} klatek")
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for img in result:
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img_skeleton = crop_hand(img, detector)
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img2= cv.resize(img_skeleton,dsize=(224,224))
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#breakpoint()
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img_np = np.asarray(img2)
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classification = classify(img_np[:,:,::-1], model)
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st.image(img_skeleton[:,:,::-1])
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st.write(classification)
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