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Browse files- requirements.txt +1 -1
- run.ipynb +1 -1
- run.py +1 -3
requirements.txt
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matplotlib
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numpy
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https://gradio-main-build.s3.amazonaws.com/
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matplotlib
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numpy
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https://gradio-main-build.s3.amazonaws.com/b4173886bab24d47bef9936a96801ce6ac6aba0e/gradio-3.36.0-py3-none-any.whl
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run.ipynb
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{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: plot_component"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio matplotlib numpy"]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import gradio as gr \n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "Fs = 8000\n", "f = 5\n", "sample = 8000\n", "x = np.arange(sample)\n", "y = np.sin(2 * np.pi * f * x / Fs)\n", "plt.plot(x, y)\n", "\n", "
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{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: plot_component"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio matplotlib numpy"]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import gradio as gr \n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "Fs = 8000\n", "f = 5\n", "sample = 8000\n", "x = np.arange(sample)\n", "y = np.sin(2 * np.pi * f * x / Fs)\n", "plt.plot(x, y)\n", "\n", "with gr.Blocks() as demo:\n", " gr.Plot(value=plt)\n", "\n", "demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
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run.py
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@@ -9,9 +9,7 @@ x = np.arange(sample)
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y = np.sin(2 * np.pi * f * x / Fs)
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plt.plot(x, y)
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with gr.Blocks(css=css) as demo:
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gr.Plot(value=plt)
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demo.launch()
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y = np.sin(2 * np.pi * f * x / Fs)
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plt.plot(x, y)
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with gr.Blocks() as demo:
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gr.Plot(value=plt)
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demo.launch()
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