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Upload 3 files
Browse files- app.ipynb +44 -66
- app.py +0 -1
- requirements.txt +9 -1
app.ipynb
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"metadata": {},
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"outputs": [],
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"source": [
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"#|default_exp app
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"import librosa.display\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"from functools import partial\n",
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"from pathlib import Path\n",
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"import pandas as pd\n",
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"import librosa\n",
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"from scipy.io import wavfile\n",
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"import gradio as gr
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]
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"cell_type": "code",
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"metadata": {},
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"source": [
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"cell_type": "code",
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"outputs": [
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"text/plain": [
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"<fastai.learner.Learner at
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"execution_count":
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"PILImage mode=RGB size=1200x800"
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"source": [
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"pred,pred_idx,probs = learn.predict('brass_acoustic_006-065-127.png')"
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"cell_type": "code",
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"execution_count":
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'Brass':
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" 'Flute': 0.
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" 'Guitar':
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" 'Keyboard':
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" 'Mallet':
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" 'Reed':
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" 'String': 1.
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" 'Vocal':
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"execution_count":
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"cell_type": "code",
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Traceback (most recent call last):\n",
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" File \"/Users/unnikrishnannambiar/anaconda3/lib/python3.9/site-packages/gradio/routes.py\", line 394, in run_predict\n",
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" output = await app.get_blocks().process_api(\n",
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" File \"/Users/unnikrishnannambiar/anaconda3/lib/python3.9/site-packages/gradio/blocks.py\", line 1075, in process_api\n",
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" result = await self.call_function(\n",
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" File \"/Users/unnikrishnannambiar/anaconda3/lib/python3.9/site-packages/gradio/blocks.py\", line 884, in call_function\n",
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" prediction = await anyio.to_thread.run_sync(\n",
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" File \"/Users/unnikrishnannambiar/anaconda3/lib/python3.9/site-packages/anyio/to_thread.py\", line 31, in run_sync\n",
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" return await get_asynclib().run_sync_in_worker_thread(\n",
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" File \"/Users/unnikrishnannambiar/anaconda3/lib/python3.9/site-packages/anyio/_backends/_asyncio.py\", line 937, in run_sync_in_worker_thread\n",
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" return await future\n",
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" File \"/Users/unnikrishnannambiar/anaconda3/lib/python3.9/site-packages/anyio/_backends/_asyncio.py\", line 867, in run\n",
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" result = context.run(func, *args)\n",
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" File \"/var/folders/tt/mvwksx9j26jc7y2pzqs4hc5w0000gn/T/ipykernel_80180/1944337707.py\", line 5, in classify_aud\n",
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" log_mel_spec_tfm(aud)\n",
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" File \"/var/folders/tt/mvwksx9j26jc7y2pzqs4hc5w0000gn/T/ipykernel_80180/1469699344.py\", line 3, in log_mel_spec_tfm\n",
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" y, sr = librosa.load(fname, mono=True)\n",
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" File \"/Users/unnikrishnannambiar/anaconda3/lib/python3.9/site-packages/librosa/util/decorators.py\", line 88, in inner_f\n",
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" return f(*args, **kwargs)\n",
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" File \"/Users/unnikrishnannambiar/anaconda3/lib/python3.9/site-packages/librosa/core/audio.py\", line 164, in load\n",
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" y, sr_native = __soundfile_load(path, offset, duration, dtype)\n",
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" File \"/Users/unnikrishnannambiar/anaconda3/lib/python3.9/site-packages/librosa/core/audio.py\", line 195, in __soundfile_load\n",
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" context = sf.SoundFile(path)\n",
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" File \"/Users/unnikrishnannambiar/anaconda3/lib/python3.9/site-packages/soundfile.py\", line 658, in __init__\n",
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" self._file = self._open(file, mode_int, closefd)\n",
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" File \"/Users/unnikrishnannambiar/anaconda3/lib/python3.9/site-packages/soundfile.py\", line 1212, in _open\n",
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" raise TypeError(\"Invalid file: {0!r}\".format(self.name))\n",
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"TypeError: Invalid file: (16000, array([28, 40, 27, ..., 0, 0, 0], dtype=int16))\n"
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]
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}
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],
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"source": [
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"from nbdev.export import nb_export\n",
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"from nbdev.release import write_requirements\n",
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"metadata": {},
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"outputs": [],
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"source": [
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"#|default_exp app"
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"cell_type": "code",
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"execution_count": 2,
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"outputs": [],
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"source": [
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"#|export\n",
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"from fastai.vision.all import *\n",
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"import librosa.display\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"import pandas as pd\n",
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"import librosa\n",
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"from scipy.io import wavfile\n",
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"import gradio as gr "
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"<fastai.learner.Learner at 0x7f84b9711220>"
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"execution_count": 4,
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"PILImage mode=RGB size=1200x800"
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"text": [
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"[W NNPACK.cpp:53] Could not initialize NNPACK! Reason: Unsupported hardware.\n"
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"source": [
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"learn.remove_cb(ProgressCallback)\n",
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"pred,pred_idx,probs = learn.predict('brass_acoustic_006-065-127.png')"
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"outputs": [
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"data": {
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"text/plain": [
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"{'Brass': 1.0856560038519092e-05,\n",
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" 'Flute': 0.9999878406524658,\n",
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" 'Guitar': 5.949047504616445e-11,\n",
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" 'Keyboard': 1.094620643016242e-07,\n",
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" 'Mallet': 1.3334407356069278e-08,\n",
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" 'Reed': 2.7653837553209826e-10,\n",
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" 'String': 1.1356026163866773e-07,\n",
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" 'Vocal': 1.0655742244125577e-06}"
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"source": [
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"from nbdev.export import nb_export\n",
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"from nbdev.release import write_requirements\n",
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app.py
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import librosa.display
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import matplotlib.pyplot as plt
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import numpy as np
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from functools import partial
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import pandas as pd
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import librosa
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from scipy.io import wavfile
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import librosa.display
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import matplotlib.pyplot as plt
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import numpy as np
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import pandas as pd
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import librosa
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from scipy.io import wavfile
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requirements.txt
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fastai
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librosa
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matplotlib
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numpy
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functools
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pandas
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librosa
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scipy
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gradio
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