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.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
+model.keras filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,48 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Sun Nov  2 22:59:41 2025
+
+@author: mathe
+"""
+
+import gradio as gr
+import numpy as np
+from PIL import Image
+import tensorflow as tf
+
+# === CONFIGURAÇÕES ===
+IMG_SIZE = 224
+CLASS_NAMES = ["gato", "cachorro"]  # mesma ordem do treino (0=cat, 1=dog)
+
+# === CARREGAR MODELO ===
+model = tf.keras.models.load_model("model.keras")
+
+# === FUNÇÃO DE PREVISÃO ===
+def preprocess_pil(img: Image.Image):
+    img = img.convert("RGB").resize((IMG_SIZE, IMG_SIZE))
+    arr = np.array(img, dtype=np.float32)
+    # MobileNetV2 preprocess (como no treino)
+    arr = tf.keras.applications.mobilenet_v2.preprocess_input(arr)
+    arr = np.expand_dims(arr, axis=0)
+    return arr
+
+def predict(img: Image.Image):
+    x = preprocess_pil(img)
+    probs = model.predict(x)[0]  # [p_cat, p_dog]
+    return {
+        CLASS_NAMES[0]: float(probs[0]),
+        CLASS_NAMES[1]: float(probs[1])
+    }
+
+# === INTERFACE GRADIO ===
+demo = gr.Interface(
+    fn=predict,
+    inputs=gr.Image(type="pil", label="Envie uma imagem"),
+    outputs=gr.Label(num_top_classes=2),
+    title="Classificador de Gatos vs. Cães 🐱🐶",
+    description="Modelo treinado com MobileNetV2 (Transfer Learning, TensorFlow)."
+)
+
+# === EXECUÇÃO LOCAL OU NO SPACE ===
+if __name__ == "__main__":
+    demo.launch()

model.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:109ec1bd3ddd598830d804af3168c9fccf2407354f17d59438c89b6f53accbde
+size 9659576

requirements.txt

@@ -0,0 +1,4 @@
+gradio>=4.44
+tensorflow==2.19.0
+pillow
+numpy