diff --git a/PyHa_Tutorial.ipynb b/PyHa_Tutorial.ipynb
index 63e9417..0b52931 100644
--- a/PyHa_Tutorial.ipynb
+++ b/PyHa_Tutorial.ipynb
@@ -58,29 +58,29 @@
"#}\n",
"\n",
"# Example Parameters for Microfaune\n",
- "isolation_parameters = {\n",
- " \"model\" : \"microfaune\",\n",
- " \"technique\" : \"steinberg\",\n",
- " \"threshold_type\" : \"median\",\n",
- " \"threshold_const\" : 2.0,\n",
- " \"threshold_min\" : 0.0,\n",
- " \"window_size\" : 2.0,\n",
- " \"chunk_size\" : 5.0,\n",
- " \"verbose\" : True,\n",
- " \"write_confidence\" : True\n",
- "}\n",
+ "# isolation_parameters = {\n",
+ "# \"model\" : \"microfaune\",\n",
+ "# \"technique\" : \"steinberg\",\n",
+ "# \"threshold_type\" : \"median\",\n",
+ "# \"threshold_const\" : 2.0,\n",
+ "# \"threshold_min\" : 0.0,\n",
+ "# \"window_size\" : 2.0,\n",
+ "# \"chunk_size\" : 5.0,\n",
+ "# \"verbose\" : True,\n",
+ "# \"write_confidence\" : True\n",
+ "# }\n",
"\n",
"# Example parameters for TweetyNET\n",
- "#isolation_parameters = {\n",
- "# \"model\" : \"tweetynet\",\n",
- "# \"tweety_output\": True,\n",
- "# \"technique\" : \"steinberg\",\n",
- "# \"threshold_type\" : \"median\",\n",
- "# \"threshold_const\" : 2.0,\n",
- "# \"threshold_min\" : 0.0,\n",
- "# \"window_size\" : 2.0,\n",
- "# \"chunk_size\" : 5.0\n",
- "#}\n",
+ "isolation_parameters = {\n",
+ " \"model\" : \"tweetynet\",\n",
+ " \"tweety_output\": True,\n",
+ " \"technique\" : \"steinberg\",\n",
+ " \"threshold_type\" : \"median\",\n",
+ " \"threshold_const\" : 2.0,\n",
+ " \"threshold_min\" : 0.0,\n",
+ " \"window_size\" : 2.0,\n",
+ " \"chunk_size\" : 5.0\n",
+ "}\n",
"\n",
"# Example parameters for FG-BG Separation\n",
"# isolation_parameters = {\n",
@@ -123,27 +123,211 @@
"metadata": {
"scrolled": true
},
+ "outputs": [],
+ "source": [
+ "automated_df = generate_automated_labels(path,isolation_parameters);"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
"outputs": [
{
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "1/1 [==============================] - 1s 567ms/step\n",
- "1/1 [==============================] - 1s 575ms/step\n",
- "1/1 [==============================] - 0s 421ms/step\n",
- "1/1 [==============================] - 0s 279ms/step\n",
- "1/1 [==============================] - 0s 341ms/step\n",
- "1/1 [==============================] - 0s 126ms/step\n",
- "1/1 [==============================] - 0s 302ms/step\n",
- "1/1 [==============================] - 0s 337ms/step\n",
- "1/1 [==============================] - 1s 574ms/step\n",
- "1/1 [==============================] - 0s 456ms/step\n",
- "1/1 [==============================] - 0s 174ms/step\n"
- ]
+ "data": {
+ "text/html": [
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+ "metadata": {},
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}
],
"source": [
- "automated_df = generate_automated_labels(path,isolation_parameters);"
+ "automated_df"
]
},
{
@@ -155,7 +339,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 6,
"metadata": {},
"outputs": [
{
@@ -201,15 +385,15 @@
" \n",
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@@ -217,13 +401,13 @@
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"\n",
- " Q3 MAX \n",
- "0 9.224694 55.420816 "
+ " Q3 MAX \n",
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]
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+ "execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
@@ -241,7 +425,7 @@
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{
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+ "execution_count": 7,
"metadata": {},
"outputs": [
{
@@ -272,7 +456,6 @@
" DURATION | \n",
" SAMPLE RATE | \n",
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@@ -318,7 +498,6 @@
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- " 0.799775 | \n",
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@@ -329,7 +508,6 @@
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- " 0.799775 | \n",
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@@ -340,10 +518,9 @@
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+ " 124 | \n",
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" 0 | \n",
@@ -351,10 +528,9 @@
" 3.0 | \n",
" 44100 | \n",
" bird | \n",
- " 0.037936 | \n",
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+ " 125 | \n",
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@@ -362,10 +538,9 @@
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+ " 126 | \n",
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@@ -373,10 +548,9 @@
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@@ -395,11 +568,10 @@
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" 44100 | \n",
" bird | \n",
- " 0.818890 | \n",
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- "185 rows × 8 columns
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+ "129 rows × 7 columns
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""
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@@ -410,29 +582,29 @@
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+ " MANUAL ID \n",
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]
},
- "execution_count": 6,
+ "execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
@@ -450,7 +622,7 @@
},
{
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- "execution_count": 7,
+ "execution_count": 8,
"metadata": {},
"outputs": [
{
@@ -641,7 +813,7 @@
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]
},
- "execution_count": 7,
+ "execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
@@ -654,7 +826,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 9,
"metadata": {},
"outputs": [
{
@@ -722,7 +894,7 @@
"0 1.767475 3.1199 "
]
},
- "execution_count": 8,
+ "execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
@@ -740,12 +912,12 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 10,
"metadata": {},
"outputs": [
{
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",
+ "image/png": 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",
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