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.gitattributes

@@ -33,3 +33,6 @@ 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
+kia_mnist_keras_model.keras filter=lfs diff=lfs merge=lfs -text
+pokemon-model_transferlearning.keras filter=lfs diff=lfs merge=lfs -text
+pokemon_model_transferlearning.keras filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,13 +1,12 @@
 ---
-title: Ki
-emoji: 🌍
-colorFrom: gray
-colorTo: blue
+title: Mnist
+emoji: 🐠
+colorFrom: pink
+colorTo: pink
 sdk: gradio
-sdk_version: 4.27.0
+sdk_version: 4.21.0
 app_file: app.py
 pinned: false
-license: mit
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,32 @@
+import gradio as gr
+import tensorflow as tf
+from PIL import Image
+import numpy as np
+
+# Load your custom regression model
+model_path = "pokemon_model_transferlearning.keras"
+model = tf.keras.models.load_model(model_path)
+
+labels = ['Wartortle', 'Weedle', 'Weepinbell', 'Weezing']
+
+# Define regression function
+def predict_regression(image):
+    # Preprocess image
+    image = Image.fromarray(image.astype('uint8'))  # Convert numpy array to PIL image
+    image = image.resize((28, 28)).convert('L') #resize the image to 28x28 and converts it to gray scale
+    image = np.array(image)
+    print(image.shape)
+    # Predict
+    prediction = model.predict(image[None, ...])  # Assuming single regression value
+    confidences = {labels[i]: np.round(float(prediction[0][i]), 2) for i in range(len(labels))}
+    return confidences
+
+# Create Gradio interface
+input_image = gr.Image()
+output_text = gr.Textbox(label="Predicted Value")
+interface = gr.Interface(fn=predict_regression, 
+                         inputs=input_image, 
+                         outputs=gr.Label(),
+                         examples=["images/wartortle.jpg", "images/weedle.jpg", "images/weepinbell.jpg", "images/weezing.jpg"],   
+                         description="A simple mlp classification model for image classification using the mnist dataset.")
+interface.launch()

pokemon_model_transferlearning.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:3ee93d0b0843ac45aa439ce6b9f1a0180459cf7a4bef952519624eeca74e60e5
+size 250584688

requirements.txt

@@ -0,0 +1 @@
+tensorflow