{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "from src.keypoint_extractor import KeypointExtractor\n", "\n", "# reload modules\n", "%load_ext autoreload" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "video_name = 'C!3_20230225181728393157_8PWYR.mp4'" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "# extract keypoints\n", "keypoint_extractor = KeypointExtractor('data/fingerspelling/data/')" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "INFO: Created TensorFlow Lite XNNPACK delegate for CPU.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "drawing\n" ] }, { "data": { "text/html": [ "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "from IPython.display import HTML\n", "from base64 import b64encode\n", "import mediapy as media\n", "%matplotlib inline\n", "\n", "# Define the frames per second (fps) and duration of the video\n", "fps = 25\n", "duration = 10\n", "\n", "# Create a dummy video of random noise\n", "_, video_frames = keypoint_extractor.extract_keypoints_from_video(video_name, draw=True)\n", "\n", "# Convert the video to a numpy array\n", "video = np.array(video_frames)\n", "media.show_video(video, height=400, codec='gif', fps=4)\n" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from src.model import SPOTER\n", "from src.identifiers import LANDMARKS\n", "import torch\n", "\n", "spoter_model = SPOTER(num_classes=5, hidden_dim=len(LANDMARKS) *2)\n", "spoter_model.load_state_dict(torch.load('models/spoter_40.pth'))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "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": "3.8.10" }, "orig_nbformat": 4, "vscode": { "interpreter": { "hash": "31f2aee4e71d21fbe5cf8b01ff0e069b9275f58929596ceb00d14d90e3e16cd6" } } }, "nbformat": 4, "nbformat_minor": 2 }