Spaces:
Runtime error
Runtime error
Commit
·
721a875
1
Parent(s):
dbf707c
Update app.py
Browse files
app.py
CHANGED
|
@@ -5,14 +5,16 @@ from transformers import pipeline
|
|
| 5 |
from PIL import Image
|
| 6 |
import time
|
| 7 |
|
| 8 |
-
|
| 9 |
-
'Starting a long computation...'
|
| 10 |
pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
|
| 11 |
|
| 12 |
st.title("Hot Dog? Or Not?")
|
| 13 |
|
| 14 |
file_name = st.file_uploader("Upload a hot dog candidate image")
|
| 15 |
|
|
|
|
|
|
|
|
|
|
|
|
|
| 16 |
if file_name is not None:
|
| 17 |
col1, col2 = st.columns(2)
|
| 18 |
|
|
@@ -21,20 +23,9 @@ if file_name is not None:
|
|
| 21 |
predictions = pipeline(image)
|
| 22 |
|
| 23 |
col2.header("Probabilities")
|
| 24 |
-
for p in predictions:
|
| 25 |
-
col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")
|
| 26 |
-
|
| 27 |
-
|
| 28 |
-
# Add a placeholder
|
| 29 |
-
latest_iteration = st.empty()
|
| 30 |
-
bar = st.progress(0)
|
| 31 |
-
|
| 32 |
-
for i in range(100):
|
| 33 |
-
# Update the progress bar with each iteration.
|
| 34 |
-
latest_iteration.text(f'Iteration {i+1}')
|
| 35 |
-
bar.progress(i + 1)
|
| 36 |
-
time.sleep(0.1)
|
| 37 |
-
|
| 38 |
-
|
| 39 |
|
| 40 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 5 |
from PIL import Image
|
| 6 |
import time
|
| 7 |
|
|
|
|
|
|
|
| 8 |
pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog")
|
| 9 |
|
| 10 |
st.title("Hot Dog? Or Not?")
|
| 11 |
|
| 12 |
file_name = st.file_uploader("Upload a hot dog candidate image")
|
| 13 |
|
| 14 |
+
# Add a placeholder
|
| 15 |
+
latest_iteration = st.empty()
|
| 16 |
+
bar = st.progress(0)
|
| 17 |
+
|
| 18 |
if file_name is not None:
|
| 19 |
col1, col2 = st.columns(2)
|
| 20 |
|
|
|
|
| 23 |
predictions = pipeline(image)
|
| 24 |
|
| 25 |
col2.header("Probabilities")
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 26 |
|
| 27 |
+
i = 0
|
| 28 |
+
for p in predictions:
|
| 29 |
+
bar.progress(i + 1)
|
| 30 |
+
time.sleep(0.1)
|
| 31 |
+
col2.subheader(f"{ p['label'] }: { round(p['score'] * 100, 1)}%")
|