Upload 3 files

Primera version

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+pizza_vs_steak_gdct_intento1.keras filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,35 @@
+# -*- coding: utf-8 -*-
+"""pizzasteakui.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1XnRBo2y4xWrz-NBRR5hd8jV-PbNvbvbK
+"""
+
+import gradio as gr
+import numpy as np
+from PIL import Image
+import tensorflow as tf
+
+modelo = tf.keras.models.load_model("./pizza_vs_steak_gdct_intento1.keras")
+
+# prompt: usando gradio, generar una interfaz para subir una imagen
+
+import numpy as np
+def predict_image(img):
+    img = Image.fromarray(img.astype('uint8'), 'RGB') # Ensure image is in correct format
+    img = img.resize((128, 128)) # Resize to model input size
+    img_array = np.array(img) / 255.0 # Normalize
+    img_array = np.expand_dims(img_array, axis=0) # Add batch dimension
+    prediction = modelo.predict(img_array)
+    print(prediction)
+    # Assuming the model outputs a single value probability for one class (e.g., steak)
+    # You might need to adjust this based on your model's output layer
+    if prediction[0] > 0.5:
+        return "Steak"
+    else:
+        return "Pizza"
+
+iface = gr.Interface(fn=predict_image, inputs="image", outputs="text", title="Pizza vs Steak Classifier")
+iface.launch()

pizza_vs_steak_gdct_intento1.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1d3fc5a584db7fe352515a6e835f49dccd44d113c3253f6fa5fc76bb740d8f01
+size 17060466

requirements.txt

@@ -0,0 +1,4 @@
+gradio
+tensorflow
+numpy
+PIL