Spaces:
Sleeping
Sleeping
File size: 871 Bytes
03a6314 a86dc43 b70ea9a 7ac435e a86dc43 62a0150 a9a7711 03a6314 a86dc43 542db5b a86dc43 542db5b 774282d a86dc43 b7be4ea 03a6314 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 |
import tf_keras as keras
import gradio as gr
import cv2
import os
from dotenv import load_dotenv
load_dotenv()
print(os.listdir('./model'))
used_model = keras.models.load_model('./model')
new_classes = ['blight', 'common_rust', 'gray_leaf_spot','healthy']
def classify_image(img_dt):
img_dt = cv2.resize(img_dt,(256,256))
img_dt = img_dt.reshape((-1,256,256,3))
prediction = used_model.predict(img_dt).flatten()
confidences = {new_classes[i]: float(prediction[i]) for i in range (4) }
return confidences
with gr.Blocks() as demo:
signal = gr.Markdown(''' Welcome to Maize Classifier,This model can identify if a leaf is
**HEALTHY**, has **COMMON RUST**, **BLIGHT** or **GRAY LEAF SPOT**''')
with gr.Row():
inp = gr.Image()
out = gr.Label()
inp.upload(fn= classify_image, inputs = inp, outputs = out)
demo.launch() |