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satnogs-wut
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Code Issues 6 Releases Activity

wut-web-dev cruft tests

master
ml server 2020-01-23 14:07:31 -07:00
parent 71ce17de48
commit 530694c0d8
1 changed files with 69 additions and 11 deletions
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80
notebooks/wut-web-dev.ipynb
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@ -20,6 +20,7 @@
"import tensorflow as tf\n",
"import numpy as np\n",
"from IPython.display import display, Image\n",
"from IPython.utils import text\n",
"from tensorflow.python.keras.models import load_model\n",
"from tensorflow.python.keras.preprocessing.image import ImageDataGenerator\n",
"from ipywidgets import interact, interactive, fixed, interact_manual\n",
@ -82,6 +83,7 @@
"metadata": {},
"outputs": [],
"source": [
"%%capture\n",
"n=0\n",
"random.seed();\n",
"for root, dirs, files in os.walk(sample_dir):\n",
@ -98,8 +100,17 @@
"metadata": {},
"outputs": [],
"source": [
"model = load_model(model_file)\n",
"\n",
"%%capture\n",
"model = load_model(model_file)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%%capture\n",
"test_image_generator = ImageDataGenerator(\n",
" rescale=1./255\n",
")\n",
@ -107,24 +118,52 @@
" directory=test_dir,\n",
" target_size=(IMG_HEIGHT, IMG_WIDTH),\n",
" shuffle=True,\n",
" class_mode='binary')\n",
"\n",
" class_mode='binary')"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%%capture\n",
"prediction = model.predict(\n",
" x=test_data_gen,\n",
" verbose=0\n",
")\n",
"predictions=[]\n",
"prediction_bool = (prediction >0.8)\n",
"predictions = prediction_bool.astype(int)\n",
"if prediction_bool[0] == False:\n",
" rating = 'bad'\n",
"else:\n",
" rating = 'good'\n",
"print('Observation: %s' % (rating))\n",
"\n",
"predictions = prediction_bool.astype(int)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"shutil.rmtree(test_dir)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"waterfallpng=os.path.basename(rfile)\n",
"print('Random waterfall:', waterfallpng)\n",
"f=text.EvalFormatter()\n",
"obsid=(f.format(\"{waterfall[slice(10,17)]}\", waterfall=waterfallpng))\n",
"print('Observation URL: https://network.satnogs.org/observations/{}'.format(obsid))\n",
"if prediction_bool[0] == False:\n",
" rating = 'BAD'\n",
"else:\n",
" rating = 'GOOD'\n",
"print('AI Observation rating: %s' % (rating))"
]
},
{
"cell_type": "code",
"execution_count": null,
@ -401,6 +440,25 @@
"print(text.marquee('wut?',40,'*'))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"a = input()\n",
"print(a)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"print('mkay')"
]
},
{
"cell_type": "code",
"execution_count": null,