Delete application.py

application.py

@@ -1,19 +0,0 @@
-import tensorflow as tf 
-import gradio as gr
-import cv2
-import numpy as np 
-
-new_model = tf.keras.models.load_model('breedclassification.h5')
-
-def predict_classes(link): 
-    img = cv2.resize(link,(224,224))
-    img = img/255
-    img = img.reshape(-1,224,224,3)   
-    pred = np.round(new_model.predict(img)).argmax(axis = 1)
-    dic = {0: 'Herding breed', 1: 'Hound breed', 2: 'Non sporting breed', 3: 'Terrior breed', 4:'working breed', 5: 'sporting breed', 6: 'toy breed'}
-    print(dic.get(int(pred)))
-    a = dic.get(int(pred))
-    return a
-    
-label = gr.outputs.Label(num_top_classes=7)
-gr.Interface(fn=predict_classes, inputs='image', outputs=label,interpretation='default',  title = 'Breed Classification detection ',  description = 'It will classify 7 different species: You can drage the images from google. 1. Terrier 2. Toy 3. Working 4. Sporting 5. Hound 6. Herding 7. Non sporting Group ').launch()