Upload 4 files

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+model.keras filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,35 @@
+import streamlit as st
+import numpy as np
+import tensorflow as tf
+from PIL import Image
+
+# Modeli yükleme
+model = tf.keras.models.load_model('model.keras')
+
+# Sınıf isimleri
+class_names = [
+    'T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat',
+    'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot'
+]
+
+# Uygulama başlığı
+st.title('Fashion MNIST Modeli ile Tahmin')
+
+# Kullanıcıdan resim yükleme
+uploaded_file = st.file_uploader("Bir resim yükleyin (28x28 boyutunda, gri tonlamalı)", type=["png", "jpg", "jpeg"])
+
+if uploaded_file is not None:
+    # Resmi yükleme ve ön işleme
+    image = Image.open(uploaded_file).convert('L')  # Gri tonlamalı
+    image = image.resize((28, 28))
+    image_array = np.array(image)
+    image_array = image_array.astype('float32') / 255.0
+    image_array = image_array.reshape(1, 28, 28)  # Modelin beklediği şekil
+
+    # Tahmin yapma
+    predictions = model.predict(image_array)
+    predicted_class = np.argmax(predictions, axis=1)
+
+    # Sonuçları gösterme
+    st.image(image, caption='Yüklenen Resim', use_column_width=True)
+    st.write(f'Tahmin Edilen Sınıf: {class_names[predicted_class[0]]}')

model.h5

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d9fd610b3a134e33945efdee35e949f31d8167d64f90d39ba4d4d3f7ff7ff57a
+size 1089512

model.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7bb738294ab2f474e794b345fa1bd82c7334d75954575d4e40c8565efd10d15d
+size 1085180

requirements.txt

@@ -0,0 +1,7 @@
+streamlit
+tensorflow
+opencv-python
+scikit-learn
+torch
+torchvision
+matplotlib