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  1. app.py +31 -0
  2. cinsiyet_2.h5 +3 -0
  3. requirements.txt +2 -0
app.py ADDED
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+ import streamlit as st
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+ from tensorflow.keras.models import load_model
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+ from PIL import Image
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+ import numpy as np
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+
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+ model=load_model("cinsiyet_2.h5")
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+
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+ def process_image(img):
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+ img=img.resize((224,224))
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+ img=np.array(img)
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+ img=img/255.0
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+ img=np.expand_dims(img,axis=0)
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+ return img
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+
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+ st.title("Uzum siniflandirma modeli")
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+ st.write("Resim sec model hangi uzum sinifinda oldugunu tahmin etsin")
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+
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+ file=st.file_uploader("Bir resim sec",type=["jpeg","jpg","png"])
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+
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+ if file is not None:
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+ img=Image.open(file)
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+ st.image(img,caption="yuklenen resim")
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+ image=process_image(img)
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+ prediction=model.predict(image)
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+ predicted_class=np.argmax(prediction)
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+
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+ class_names={1:"women",
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+ 0:"men"
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+ }
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+
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+ st.write(class_names[predicted_class])
cinsiyet_2.h5 ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:e37c663b4478feaee7ae6695e56869e2b02ad36ec1b958565ef809fb4db5e102
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+ size 367280088
requirements.txt ADDED
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+ streamlit
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+ tensorflow