'Let's try this'
Browse files- LeopardCheetah.pkl +3 -0
- app.py +27 -0
LeopardCheetah.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:20489459d404e8699b79d9bc9f2b60fd77fa6413f1d583ed26b79084dc33d748
|
| 3 |
+
size 46994401
|
app.py
ADDED
|
@@ -0,0 +1,27 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
#|export
|
| 2 |
+
|
| 3 |
+
from fastcore.all import *
|
| 4 |
+
from fastai.vision.all import *
|
| 5 |
+
from fastbook import load_learner
|
| 6 |
+
import gradio as gr
|
| 7 |
+
|
| 8 |
+
inf = load_learner('LeopardCheetah.pkl')
|
| 9 |
+
|
| 10 |
+
categories = ('Cheetah','Images','Leopard')
|
| 11 |
+
|
| 12 |
+
def classify_img(img):
|
| 13 |
+
pred, idx, probs = inf.predict(img)
|
| 14 |
+
return dict(zip(categories,map(float,probs)))
|
| 15 |
+
|
| 16 |
+
#|export
|
| 17 |
+
|
| 18 |
+
#This creates the gradio interface
|
| 19 |
+
|
| 20 |
+
image = gr.Image(shape=(192,192))
|
| 21 |
+
label = gr.outputs.Label()
|
| 22 |
+
|
| 23 |
+
examples = ['cheetah.jpg','leopard.jpg','img.jpg']
|
| 24 |
+
|
| 25 |
+
intf = gr.Interface(fn = classify_img, inputs=image,outputs=label,examples = examples)
|
| 26 |
+
|
| 27 |
+
intf.launch(inline=False)
|