Usando Blocks

Ahora usando blocks para llamar a gradio y poder manipular los botones

app.py

@@ -1,26 +1,22 @@
 # AUTOGENERATED! DO NOT EDIT! File to edit: Todo_para_ml_imagenes.ipynb.
 
 # %% auto 0
-__all__ = ['plt', 'path', 'learn_inf', 'labels', 'demo', 'predict']
+__all__ = ['plt', 'path', 'learn_inf', 'labels', 'predict', 'clear']
 
 # %% Todo_para_ml_imagenes.ipynb 4
 from pathlib import Path
-#from fastcore.all import *
 from fastai.vision.all import *
-#from fastai.vision.widgets import *
-
 import pathlib
 plt = platform.system()
 if plt != 'Windows': pathlib.WindowsPath = pathlib.PosixPath 
 
-# %% Todo_para_ml_imagenes.ipynb 28
+# %% Todo_para_ml_imagenes.ipynb 29
 path = Path()
-#path.ls(file_exts='.pkl')
 
-# %% Todo_para_ml_imagenes.ipynb 30
+# %% Todo_para_ml_imagenes.ipynb 31
 learn_inf = load_learner(path/'PapaRod.pkl')
 
-# %% Todo_para_ml_imagenes.ipynb 54
+# %% Todo_para_ml_imagenes.ipynb 55
 import gradio as gr
 
 labels = learn_inf.dls.vocab
@@ -29,10 +25,19 @@ def predict(img):
     pred,pred_idx,probs = learn_inf.predict(img)
     return {labels[i]: float(probs[i]) for i in range(len(labels))}
 
-# %% Todo_para_ml_imagenes.ipynb 56
-demo = gr.Interface(
-    predict, 
-    gr.Image(source="webcam", streaming=False), 
-    outputs=gr.components.Label(num_top_classes=3),
-    live=True
-).launch()
+def clear():
+    return None
+
+
+
+# %% Todo_para_ml_imagenes.ipynb 58
+with gr.Blocks() as demo:
+    gr.Markdown("## Tómate una foto a ver si te reconoce.")
+    with gr.Row():
+        image_input = gr.Image(source="webcam", streaming=False)
+        output = gr.components.Label(num_top_classes=3)
+    image_button = gr.Button("¿Quién es?")
+
+    image_button.click(predict, inputs=image_input, outputs=output)
+
+demo.launch()