Spaces:
Runtime error
Runtime error
File size: 1,156 Bytes
4a1f11f 08b90ae 4a1f11f 08b90ae 655a404 08b90ae 4a1f11f 08b90ae bcc3395 08b90ae bcc3395 08b90ae | 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 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | import gradio as gr
from fastai.vision.all import *
import os
def is_cat(x):
if x[0].isupper():
return 'cat'
else:
return 'dog'
learn_inference = load_learner('is_Cat_resnet.pkl')
def image_mod(image):
detect, _, predict = learn_inference.predict(image)
return detect
image = gr.inputs.Image(shape=(192,192))
label = gr.outputs.Label()
examples=[
"images/db.jpg",
"images/dog2.jpg",
"images/cat3.jpg",
"images/dog4.jpg",
"images/pug1.jpg",
"images/cat2.jpg",
]
# examples=[
# os.path.join(os.path.dirname(__file__), "images/db.jpg"),
# os.path.join(os.path.dirname(__file__), "images/dog1.jpg"),
# os.path.join(os.path.dirname(__file__), "images/dog2.jpg"),
# os.path.join(os.path.dirname(__file__), "images/dog3.jpg"),
# os.path.join(os.path.dirname(__file__), "images/dog4.jpg"),
# os.path.join(os.path.dirname(__file__), "images/pug1.jpg"),
# ]
demo = gr.Interface(
image_mod,
inputs = image,
outputs = label,
examples = examples
)
if __name__ == "__main__":
demo.launch()
|