Delete old/app.py

old/app.py

@@ -1,43 +0,0 @@
-import streamlit as st
-from transformers import pipeline
-#from datasets import load_dataset, Image
-from huggingface_hub import from_pretrained_keras
-import keras
-import numpy as np
-from PIL import Image
-
-loaded_model = keras.saving.load_model("best_model.keras")
-
-uploaded_img = st.file_uploader("Upload your file here...",type=['png', 'jpeg', 'jpg'])
-
-if uploaded_img is not None:
-    st.image(uploaded_img)
-    img = Image.open(uploaded_img).resize((160, 160))
-    img = np.array(img)
-    result = loaded_model.predict(img[None,:,:])
-    st.write(f"Your prediction is: {result}")
-
-
-#model = from_pretrained_keras("jableable/road_model")
-
-#pipe = pipeline('sentiment-analysis')
-#text = st.text_area('enter some text!')
-
-#if text:
-    #out = pipe(text)
-    #st.json(out)
-
-#loaded_model = keras.saving.load_model("jableable/road_model")
-
-#model = from_pretrained_keras("keras-io/ocr-for-captcha")
-#model.summary()
-#prediction = model.predict(image)
-#prediction = tf.squeeze(tf.round(prediction))
-#print(f'The image is a {classes[(np.argmax(prediction))]}!')
-
-
-#dataset = load_dataset("beans", split="train")
-
-#loaded_img = dataset[0]["image"]
-#print(loaded_img)
-