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app.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting gradio\n",
+      "  Downloading gradio-4.31.4-py3-none-any.whl.metadata (15 kB)\n",
+      "Collecting aiofiles<24.0,>=22.0 (from gradio)\n",
+      "  Using cached aiofiles-23.2.1-py3-none-any.whl.metadata (9.7 kB)\n",
+      "Collecting altair<6.0,>=4.2.0 (from gradio)\n",
+      "  Using cached altair-5.3.0-py3-none-any.whl.metadata (9.2 kB)\n",
+      "Collecting fastapi (from gradio)\n",
+      "  Downloading fastapi-0.111.0-py3-none-any.whl.metadata (25 kB)\n",
+      "Collecting ffmpy (from gradio)\n",
+      "  Using cached ffmpy-0.3.2.tar.gz (5.5 kB)\n",
+      "  Preparing metadata (setup.py) ... \u001b[?25ldone\n",
+      "\u001b[?25hCollecting gradio-client==0.16.4 (from gradio)\n",
+      "  Downloading gradio_client-0.16.4-py3-none-any.whl.metadata (7.1 kB)\n",
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+      "Requirement already satisfied: importlib-resources<7.0,>=1.3 in /Users/mabelang/Documents/Z. AI apps/AI Task 2_Pokemon Classifier/.venv/lib/python3.12/site-packages (from gradio) (6.4.0)\n",
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+      "  Downloading orjson-3.10.3-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl.metadata (49 kB)\n",
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+      "Requirement already satisfied: requests in /Users/mabelang/Documents/Z. AI apps/AI Task 2_Pokemon Classifier/.venv/lib/python3.12/site-packages (from huggingface-hub>=0.19.3->gradio) (2.32.0)\n",
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+      "\u001b[?25hBuilding wheels for collected packages: ffmpy\n",
+      "  Building wheel for ffmpy (setup.py) ... \u001b[?25ldone\n",
+      "\u001b[?25h  Created wheel for ffmpy: filename=ffmpy-0.3.2-py3-none-any.whl size=5584 sha256=97651e6dbb547e6b91aabbc5543bdf57b24da837cbeae1b4a111522dc42924b5\n",
+      "  Stored in directory: /Users/mabelang/Library/Caches/pip/wheels/8a/63/a8/fad16a1c5c990569a478f40782ce543788ddac224288008635\n",
+      "Successfully built ffmpy\n",
+      "Installing collected packages: pytz, pydub, ffmpy, websockets, uvloop, ujson, tzdata, toolz, tomlkit, sniffio, shellingham, semantic-version, ruff, rpds-py, pyyaml, python-multipart, python-dotenv, pydantic-core, orjson, jinja2, httptools, h11, filelock, dnspython, attrs, annotated-types, aiofiles, uvicorn, referencing, pydantic, pandas, huggingface-hub, httpcore, email_validator, anyio, watchfiles, typer, starlette, jsonschema-specifications, httpx, jsonschema, gradio-client, fastapi-cli, fastapi, altair, gradio\n",
+      "Successfully installed aiofiles-23.2.1 altair-5.3.0 annotated-types-0.7.0 anyio-4.3.0 attrs-23.2.0 dnspython-2.6.1 email_validator-2.1.1 fastapi-0.111.0 fastapi-cli-0.0.4 ffmpy-0.3.2 filelock-3.14.0 gradio-4.31.4 gradio-client-0.16.4 h11-0.14.0 httpcore-1.0.5 httptools-0.6.1 httpx-0.27.0 huggingface-hub-0.23.0 jinja2-3.1.4 jsonschema-4.22.0 jsonschema-specifications-2023.12.1 orjson-3.10.3 pandas-2.2.2 pydantic-2.7.1 pydantic-core-2.18.2 pydub-0.25.1 python-dotenv-1.0.1 python-multipart-0.0.9 pytz-2024.1 pyyaml-6.0.1 referencing-0.35.1 rpds-py-0.18.1 ruff-0.4.4 semantic-version-2.10.0 shellingham-1.5.4 sniffio-1.3.1 starlette-0.37.2 tomlkit-0.12.0 toolz-0.12.1 typer-0.12.3 tzdata-2024.1 ujson-5.10.0 uvicorn-0.29.0 uvloop-0.19.0 watchfiles-0.21.0 websockets-11.0.3\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "# pip install gradio"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/mabelang/Documents/Z. AI apps/AI Task 2_Pokemon Classifier/.venv/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "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": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model_path = \"mabel_transferlearning.keras\"\n",
+    "model = tf.keras.models.load_model(model_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define the core prediction function\n",
+    "def predict_pokemons(image):\n",
+    "    # Preprocess image\n",
+    "    print(type(image))\n",
+    "    image = Image.fromarray(image.astype('uint8'))  # Convert numpy array to PIL image\n",
+    "    image = image.resize((150, 150)) #resize the image to 28x28 and converts it to gray scale\n",
+    "    image = np.array(image)\n",
+    "    image = np.expand_dims(image, axis=0) # same as image[None, ...]\n",
+    "    \n",
+    "    # Predict\n",
+    "    prediction = model.predict(image)\n",
+    "    \n",
+    "    # Apply sigmoid to get probabilities\n",
+    "    prediction_prob = tf.sigmoid(prediction).numpy()\n",
+    "\n",
+    "    p_Abra = round(prediction_prob[0][0], 2)\n",
+    "    p_Pikachu = round(prediction_prob[0][1], 2)\n",
+    "    p_Beedrill = round(prediction_prob[0][2], 2)\n",
+    "\n",
+    "    return{'Abra': p_Abra, 'Pikachu': p_Pikachu, 'Beedrill': p_Beedrill}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7863\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7863/\" 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": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Create the Gradio interface\n",
+    "input_image = gr.Image()\n",
+    "iface = gr.Interface(\n",
+    "    fn=predict_pokemons,\n",
+    "    inputs=input_image, \n",
+    "    outputs=gr.Label(),\n",
+    "    examples=[\"Abra1.png\", \"Abra2.png\", \"Abra3.jpg\", \"Beedrill1.jpg\", \"Beedrill2.jpg\", \"Beedrill3.png\", \"Pikachu1.png\", \"Pikachu2.jpg\", \"Pikachu3.png\"], \n",
+    "    description=\"Pokemon Classifier\")\n",
+    "iface.launch()"
+   ]
+  }
+ ],
+ "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": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

mabel-poke.zip

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