@ -2,10 +2,18 @@
"cells": [
"cells": [
{
{
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"cell_type": "code",
"execution_count": 2 ,
"execution_count": 1 ,
"id": "4fdb98fc-65bb-467e-be0c-168fee9b0fca",
"id": "4fdb98fc-65bb-467e-be0c-168fee9b0fca",
"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/sibscience-4/from_ssh/DroneDetector/.venv-train/lib/python3.12/site-packages/matplotlib/projections/__init__.py:63: UserWarning: Unable to import Axes3D. This may be due to multiple versions of Matplotlib being installed (e.g. as a system package and as a pip package). As a result, the 3D projection is not available.\n",
" warnings.warn(\"Unable to import Axes3D. This may be due to multiple versions of \"\n"
]
},
{
{
"name": "stdout",
"name": "stdout",
"output_type": "stream",
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@ -16,10 +24,10 @@
{
{
"data": {
"data": {
"text/plain": [
"text/plain": [
"<contextlib.ExitStack at 0x7d183e4bd22 0>"
"<contextlib.ExitStack at 0x7dbe9e0bc08 0>"
]
]
},
},
"execution_count": 2 ,
"execution_count": 1 ,
"metadata": {},
"metadata": {},
"output_type": "execute_result"
"output_type": "execute_result"
}
}
@ -64,7 +72,7 @@
},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count": 3 ,
"execution_count": 2 ,
"id": "4848b066-2e09-4c1c-b8fa-8e3fa84d907a",
"id": "4848b066-2e09-4c1c-b8fa-8e3fa84d907a",
"metadata": {},
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"outputs": [],
@ -74,7 +82,7 @@
},
},
{
{
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"execution_count": 4 ,
"execution_count": 3 ,
"id": "9267fbe1",
"id": "9267fbe1",
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"metadata": {},
"outputs": [],
"outputs": [],
@ -147,20 +155,20 @@
},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count": 12 ,
"execution_count": 16 ,
"id": "448da74a-e0ae-44d8-9877-8dd1f257a24f",
"id": "448da74a-e0ae-44d8-9877-8dd1f257a24f",
"metadata": {},
"metadata": {},
"outputs": [],
"outputs": [],
"source": [
"source": [
"selected_freq=75 0\n",
"selected_freq=240 0\n",
"\n",
"\n",
"path_to_binaries = f'/mnt/nvme1/dataset /{selected_freq}'\n",
"path_to_binaries = f'/mnt/data/Dataset/noise /{selected_freq}'\n",
"path_to_pictures = f'/mnt/nvme1/d ataset_img/noise/{selected_freq}_jpg'"
"path_to_pictures = f'/mnt/data/D ataset_img/noise/{selected_freq}_jpg'"
]
]
},
},
{
{
"cell_type": "code",
"cell_type": "code",
"execution_count": 6 ,
"execution_count": 14 ,
"id": "ac4945a8-29c4-4da4-945f-08658953e3e5",
"id": "ac4945a8-29c4-4da4-945f-08658953e3e5",
"metadata": {},
"metadata": {},
"outputs": [],
"outputs": [],
@ -170,7 +178,7 @@
},
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{
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"id": "6f226f86-5d72-4573-8af6-750128b70263",
"id": "6f226f86-5d72-4573-8af6-750128b70263",
"metadata": {},
"metadata": {},
"outputs": [
"outputs": [
@ -178,287 +186,42 @@
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{
{
@ -482,7 +245,7 @@
" continue\n",
" continue\n",
"\n",
"\n",
" files = os.listdir(filepath)\n",
" files = os.listdir(filepath)\n",
" k = max(1, int(len(files) * 0.04 ))\n",
" k = max(1, int(len(files) * 1 ))\n",
" files = random.sample(files, k)\n",
" files = random.sample(files, k)\n",
" for file in tqdm(files, desc=subdir):\n",
" for file in tqdm(files, desc=subdir):\n",
" full_input_path = filepath + file\n",
" full_input_path = filepath + file\n",
@ -542,7 +305,7 @@
],
],
"metadata": {
"metadata": {
"kernelspec": {
"kernelspec": {
"display_name": ".venv-train (3.12.3) ",
"display_name": ".venv-train",
"language": "python",
"language": "python",
"name": "python3"
"name": "python3"
},
},