Upload app.ipynb

app.ipynb

@@ -0,0 +1,157 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import gradio as gr\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "from PIL import Image"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7861\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7861/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7862\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7862/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Load your custom classification models\n",
+    "scratch_model = tf.keras.models.load_model('animal_classifier_model_scratch.keras')\n",
+    "transfer_learning_model = tf.keras.models.load_model('animal_classifier_model_transfer.keras')\n",
+    "\n",
+    "# Class names, should match your dataset\n",
+    "class_names = ['butterfly', 'cat', 'elephant', 'horse', 'squirrel']\n",
+    "\n",
+    "def classify_image(image, model):\n",
+    "    # Convert the Gradio input image to a PIL image\n",
+    "    if isinstance(image, np.ndarray):\n",
+    "        image = Image.fromarray(image.astype('uint8'), 'RGB')\n",
+    "    \n",
+    "    # Resize the image using np.resize\n",
+    "    image = np.resize(image, (300, 300, 3))  # Add the channel dimension\n",
+    "    \n",
+    "    image = image / 255.0  # Normalize the image\n",
+    "    image = np.expand_dims(image, axis=0)  # Add batch dimension\n",
+    "    \n",
+    "    # Predict the class of the image\n",
+    "    predictions = model.predict(image)\n",
+    "    \n",
+    "    # Get the indices of the top 3 predictions\n",
+    "    top_indices = np.argsort(predictions[0])[::-1][:3]\n",
+    "    \n",
+    "    # Get the corresponding class names and confidences\n",
+    "    top_classes = [class_names[i] for i in top_indices]\n",
+    "    confidences = [predictions[0][i] for i in top_indices]\n",
+    "    \n",
+    "    return {class_name: float(confidence) for class_name, confidence in zip(top_classes, confidences)}\n",
+    "\n",
+    "image_input = gr.Image()\n",
+    "label = gr.Label(num_top_classes=3)\n",
+    "\n",
+    "scratch_interface = gr.Interface(\n",
+    "    fn=lambda image: classify_image(image, scratch_model), \n",
+    "    inputs=image_input, \n",
+    "    outputs=label,\n",
+    "    title='Animal Classifier (Scratch Model)',\n",
+    "    description='Upload an image of an animal, and the classifier will tell you which animal it is, along with the confidence level of the prediction.'\n",
+    ")\n",
+    "\n",
+    "transfer_learning_interface = gr.Interface(\n",
+    "    fn=lambda image: classify_image(image, transfer_learning_model), \n",
+    "    inputs=image_input, \n",
+    "    outputs=label,\n",
+    "    title='Animal Classifier (Transfer Learning Model)',\n",
+    "    description='Upload an image of an animal, and the classifier will tell you which animal it is, along with the confidence level of the prediction.'\n",
+    ")\n",
+    "\n",
+    "scratch_interface.launch()\n",
+    "transfer_learning_interface.launch()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "venv_new",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}