Spaces:
Sleeping
Sleeping
Upload folder using huggingface_hub
Browse files- README.md +3 -9
- main.py +18 -0
- requirements.txt +6 -0
README.md
CHANGED
@@ -1,12 +1,6 @@
|
|
1 |
---
|
2 |
-
title:
|
3 |
-
|
4 |
-
colorFrom: yellow
|
5 |
-
colorTo: yellow
|
6 |
sdk: gradio
|
7 |
-
sdk_version: 4.
|
8 |
-
app_file: app.py
|
9 |
-
pinned: false
|
10 |
---
|
11 |
-
|
12 |
-
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
|
|
|
1 |
---
|
2 |
+
title: Skin_Cancer_Classifier
|
3 |
+
app_file: main.py
|
|
|
|
|
4 |
sdk: gradio
|
5 |
+
sdk_version: 4.25.0
|
|
|
|
|
6 |
---
|
|
|
|
main.py
ADDED
@@ -0,0 +1,18 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import gradio as gr
|
2 |
+
from transformers import pipeline
|
3 |
+
|
4 |
+
pipeline = pipeline("image-classification", model="jhoppanne/SkinCancerClassifier_Plain-V0")
|
5 |
+
|
6 |
+
def predict(input_img):
|
7 |
+
predictions = pipeline(input_img)
|
8 |
+
return input_img, {p["label"]: p["score"] for p in predictions}
|
9 |
+
|
10 |
+
gradio_app = gr.Interface(
|
11 |
+
predict,
|
12 |
+
inputs=gr.Image(label="Input Skin Image", sources=['upload', 'webcam'], type="pil"),
|
13 |
+
outputs=[gr.Image(label="Processed Image"), gr.Label(label="Result", num_top_classes=2)],
|
14 |
+
title="How severe is my Skin Cancer?",
|
15 |
+
)
|
16 |
+
|
17 |
+
if __name__ == "__main__":
|
18 |
+
gradio_app.launch()
|
requirements.txt
ADDED
@@ -0,0 +1,6 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# Python 3.10.14
|
2 |
+
gradio==4.25.0
|
3 |
+
transformers==4.37.2
|
4 |
+
torch
|
5 |
+
numpy
|
6 |
+
pillow==10.3.0
|