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satnogs-wut
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Code Issues 6 Releases Activity

kind of working

master
ml server 2020-01-24 18:49:02 -07:00
parent a36ab62de9
commit e78275f0c6
1 changed files with 64 additions and 27 deletions
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91
notebooks/wut-web-dev.ipynb
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@ -93,6 +93,63 @@
"model = load_model(model_file)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%%capture\n",
"def gen_image(test_data_gen,test_dir):\n",
" test_image_gen = ImageDataGenerator(rescale=1./255);\n",
" test_data_gen = test_image_gen.flow_from_directory(batch_size=1,\n",
" directory=test_dir,\n",
" target_size=(IMG_HEIGHT, IMG_WIDTH),\n",
" shuffle=True,\n",
" class_mode='binary');\n",
" return test_data_gen"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%%capture --no-stderr --no-stdout\n",
"def gen_image_tmp(obs_waterfall_path):\n",
" tmp_dir = tempfile.mkdtemp()\n",
" test_dir = os.path.join(tmp_dir)\n",
" os.makedirs(test_dir + '/unvetted', exist_ok=True)\n",
" shutil.copy(obs_waterfall_path, test_dir + '/unvetted/') \n",
" \n",
" img = im.open(obs_waterfall_path).resize( (100,200))\n",
" display(img)\n",
"\n",
" # XXX delete tmp dir down below\n",
" #print(test_dir)\n",
" #shutil.rmtree(test_dir) \n",
" return test_dir"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%%capture\n",
"def obs_wutsay(test_data_gen):\n",
" prediction = model.predict(\n",
" x=test_data_gen,\n",
" verbose=0)\n",
" predictions=[]\n",
" prediction_bool = (prediction >0.8)\n",
" predictions = prediction_bool.astype(int)\n",
" \n",
" return prediction_bool"
]
},
{
"cell_type": "code",
"execution_count": null,
@ -118,26 +175,12 @@
" \n",
" obs_waterfall=os.path.basename(obs_waterfallurl)\n",
" obs_waterfall_path = os.path.join('/srv/satnogs/download', str(obs_id), obs_waterfall)\n",
" \n",
" test_dir=gen_image_tmp(obs_waterfall_path)\n",
" test_data_gen=gen_image(obs_waterfall_path, test_dir)\n",
" \n",
" tmp_dir = tempfile.mkdtemp()\n",
" test_dir = os.path.join(tmp_dir)\n",
" os.makedirs(test_dir + '/unvetted', exist_ok=True)\n",
" shutil.copy(obs_waterfall_path, test_dir + '/unvetted/')\n",
" img = im.open(obs_waterfall_path).resize( (100,200) )\n",
" test_image_generator = ImageDataGenerator(\n",
" rescale=1./255\n",
" )\n",
" test_data_gen = test_image_generator.flow_from_directory(batch_size=1,\n",
" directory=test_dir,\n",
" target_size=(IMG_HEIGHT, IMG_WIDTH),\n",
" shuffle=True,\n",
" class_mode='binary')\n",
" prediction = model.predict(\n",
" x=test_data_gen,\n",
" verbose=0)\n",
" predictions=[]\n",
" prediction_bool = (prediction >0.8)\n",
" predictions = prediction_bool.astype(int)\n",
" prediction_bool=obs_wutsay(test_data_gen);\n",
"\n",
" print()\n",
" print('Observation ID: ', obs_id)\n",
" print('Encoding: ', obs_transmitter_mode)\n",
@ -146,19 +189,13 @@
" rating = 'bad'\n",
" else:\n",
" rating = 'good'\n",
" print('wut AI rating: %s' % (rating))\n",
" \n",
" print('wut AI rating: %s' % (rating)) \n",
" print()\n",
" if obs_transmitter_mode == 'DUV':\n",
" print(\"Using DUV training model.\")\n",
" else:\n",
" print(\"NOTE: wut has not been trained on\", obs_transmitter_mode, \"encodings.\")\n",
"\n",
" print('https://network.satnogs.org/observations/' + str(obs_id))\n",
" print()\n",
" \n",
" display(img)\n",
" shutil.rmtree(test_dir)\n",
" #!cat $obsjsonfile"
]
},
@ -168,7 +205,7 @@
"metadata": {},
"outputs": [],
"source": [
"print('Enter an Observation ID between', minobsid, 'and', maxobsid)\n",
"print('Enter an Observation ID between', minobsid, 'and', maxobsid);\n",
"wutObs_slide = wg.IntText(value='1292461');\n",
"wg.interact(wutObs, datObs=wutObs_slide);"
]