Delete cotton_app.py

cotton_app.py

@@ -1,39 +0,0 @@
-import tensorflow as tf
-model = tf.keras.models.load_model('cotton_crop.h5')
-import streamlit as st
-st.write("""
-         # Cotton crop identification
-         """
-         )
-#st.write("This is a simple image classification web app to predict rock-paper-scissor hand sign")
-file = st.file_uploader("Please upload an image file", type=["jpg", "png"])
-
-import cv2
-from PIL import Image, ImageOps
-import numpy as np
-def import_and_predict(image_data, model):
-    
-        size = (300,300)    
-        image = ImageOps.fit(image_data, size, Image.ANTIALIAS)
-        image = np.asarray(image)
-        img = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-        img_resize = (cv2.resize(img, dsize=(300, 300),    interpolation=cv2.INTER_CUBIC))/255.
-        
-        img_reshape = img_resize[np.newaxis,...]
-    
-        prediction = model.predict(img_reshape)
-        
-        return prediction
-if file is None:
-    st.text("Please upload an image file")
-else:
-    image = Image.open(file)
-    st.image(image, use_column_width=True)
-    prediction = import_and_predict(image, model)
-    
-#    if np.argmax(prediction) == 0:
-    if prediction[0][0]==1.0:
-        st.write("Cotton crop")
-    else:
-        st.write("Not a cotton crop")
-    st.write(prediction)