diff --git a/PythonAI/JupyterLab/PythonAI_5.ipynb b/PythonAI/JupyterLab/PythonAI_5.ipynb index 8e9a011..b33f330 100644 --- a/PythonAI/JupyterLab/PythonAI_5.ipynb +++ b/PythonAI/JupyterLab/PythonAI_5.ipynb @@ -1897,7 +1897,9 @@ { "cell_type": "markdown", "id": "2c041416-51ff-4b9e-bb4d-c3431fa870e7", - "metadata": {}, + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, "source": [ "# Dzień 6 - 20.05.2025" ] @@ -1905,7 +1907,9 @@ { "cell_type": "markdown", "id": "cd20cae1-be7f-49ee-b112-15f4cd9cfc6f", - "metadata": {}, + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, "source": [ "# CNN - Convolutional Neural Network\n", "## zalety \n", @@ -2364,7 +2368,9 @@ { "cell_type": "markdown", "id": "44cc5989-0cf6-49d1-8307-b9e4d2a1bbd5", - "metadata": {}, + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, "source": [ "# PyTorch" ] @@ -2677,7 +2683,9 @@ { "cell_type": "markdown", "id": "01db7828-0e98-45b9-b332-9d86a148f3cc", - "metadata": {}, + "metadata": { + "jp-MarkdownHeadingCollapsed": true + }, "source": [ "# Sieć YOLO\n", "algorytm/sieć YOLO służy do rozpoznawania obiektów znajdujących się na zdjęciach\n", @@ -2690,6 +2698,95 @@ "id": "a27ad14f-3a79-46d0-bfa6-154f85e9513a", "metadata": {}, "outputs": [], + "source": [ + "from ultralytics import YOLO\n", + "\n", + "model = YOLO(\"yolo11n.pt\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "031a2a4a-bf53-4c6a-84dd-1e8cacb8ca94", + "metadata": {}, + "outputs": [], + "source": [ + "result = model.predict('https://shropshiremammalgroup.com/wp-content/uploads/2020/05/wild-boar-forest-of-dean-robin-bennett-3.jpg?w=1024')\n", + "print(result)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6ddb0744-22b9-4c2c-bc53-d6d8c02bd83c", + "metadata": {}, + "outputs": [], + "source": [ + "from PIL import Image\n", + "\n", + "Image.fromarray(result[0].plot())" + ] + }, + { + "cell_type": "markdown", + "id": "ec06874f-c48a-43ce-b44e-364e4ed5ee37", + "metadata": {}, + "source": [ + "# RNN - Recurrent Neural Network" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "9bde4f30-f26c-4b37-bfa6-8b64460fe13d", + "metadata": {}, + "outputs": [], + "source": [ + "import tensorflow as tf\n", + "from tensorflow.keras.models import Sequential\n", + "from tensorflow.keras.layers import SimpleRNN, Embedding, Dense" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "d2e9da87-1912-466f-b902-e45130d8fd32", + "metadata": {}, + "outputs": [], + "source": [ + "vocab_size = 10000\n", + "embedding_dim = 64\n", + "sequence_length = 100" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "88156e8c-3c2a-467e-a018-a09c0f292de0", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/sasza/.local/share/virtualenvs/JupyterLab-9JRWupKp/lib/python3.12/site-packages/keras/src/layers/core/embedding.py:97: UserWarning: Argument `input_length` is deprecated. Just remove it.\n", + " warnings.warn(\n" + ] + } + ], + "source": [ + "model = Sequential()\n", + "model.add(Embedding(vocab_size, embedding_dim, input_length=sequence_length))\n", + "model.add(SimpleRNN(128))\n", + "model.add(Dense(1,activation='sigmoid'))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f976e119-8888-4316-a1b8-2352f74c42e8", + "metadata": {}, + "outputs": [], "source": [] } ],