changed apperance

Gradio_app.ipynb

@@ -2,14 +2,14 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Running on local URL:  http://127.0.0.1:7923\n",
+      "Running on local URL:  http://127.0.0.1:7860\n",
       "\n",
       "To create a public link, set `share=True` in `launch()`.\n"
      ]
@@ -17,7 +17,7 @@
     {
      "data": {
       "text/html": [
-       "<div><iframe src=\"http://127.0.0.1:7923/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+       "<div><iframe src=\"http://127.0.0.1:7860/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
       ],
       "text/plain": [
        "<IPython.core.display.HTML object>"
@@ -30,138 +30,9 @@
      "data": {
       "text/plain": []
      },
-     "execution_count": 83,
+     "execution_count": 1,
      "metadata": {},
      "output_type": "execute_result"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Starting to download inventory\n",
-      "Finished downloading inventory\n",
-      "Processing CI.CCC...\n",
-      "Downloading waveform\n",
-      "Skipping CI_CCC_2019-07-04T17:33:40.494920Z\n",
-      "Processing CI.CLC...\n",
-      "Processing CI.JRC2...\n",
-      "Reading cached waveform\n",
-      "Added CI.JRC2 to the list of waveforms\n",
-      "Processing CI.LRL...\n",
-      "Reading cached waveform\n",
-      "Added CI.LRL to the list of waveforms\n",
-      "Processing CI.MPM...\n",
-      "Reading cached waveform\n",
-      "Processing CI.Q0072...\n",
-      "Reading cached waveform\n",
-      "Processing CI.SLA...\n",
-      "Reading cached waveform\n",
-      "Added CI.SLA to the list of waveforms\n",
-      "Processing CI.SRT...\n",
-      "Reading cached waveform\n",
-      "Added CI.SRT to the list of waveforms\n",
-      "Processing CI.TOW2...\n",
-      "Reading cached waveform\n",
-      "Added CI.TOW2 to the list of waveforms\n",
-      "Processing CI.WBM...\n",
-      "Downloading waveform\n",
-      "Skipping CI_WBM_2019-07-04T17:33:40.063616Z\n",
-      "Processing CI.WCS2...\n",
-      "Downloading waveform\n",
-      "Skipping CI_WCS2_2019-07-04T17:33:40.200958Z\n",
-      "Processing CI.WMF...\n",
-      "Reading cached waveform\n",
-      "Added CI.WMF to the list of waveforms\n",
-      "Processing CI.WNM...\n",
-      "Reading cached waveform\n",
-      "Processing CI.WRC2...\n",
-      "Downloading waveform\n",
-      "Skipping CI_WRC2_2019-07-04T17:33:38.698099Z\n",
-      "Processing CI.WRV2...\n",
-      "Reading cached waveform\n",
-      "Processing CI.WVP2...\n",
-      "Downloading waveform\n",
-      "Skipping CI_WVP2_2019-07-04T17:33:39.650402Z\n",
-      "Processing NP.1809...\n",
-      "Reading cached waveform\n",
-      "Processing NP.5419...\n",
-      "Reading cached waveform\n",
-      "Processing PB.B916...\n",
-      "Reading cached waveform\n",
-      "Processing PB.B917...\n",
-      "Reading cached waveform\n",
-      "Processing PB.B918...\n",
-      "Reading cached waveform\n",
-      "Processing PB.B921...\n",
-      "Reading cached waveform\n",
-      "Starting to run predictions\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/var/folders/_g/3q5q8_dj0ydcpktxlwxb5vrh0000gq/T/ipykernel_17878/2982466024.py:225: FutureWarning: The input object of type 'Tensor' is an array-like implementing one of the corresponding protocols (`__array__`, `__array_interface__` or `__array_struct__`); but not a sequence (or 0-D). In the future, this object will be coerced as if it was first converted using `np.array(obj)`. To retain the old behaviour, you have to either modify the type 'Tensor', or assign to an empty array created with `np.empty(correct_shape, dtype=object)`.\n",
-      "  waveforms = np.array(waveforms)[selection_indexes]\n",
-      "/var/folders/_g/3q5q8_dj0ydcpktxlwxb5vrh0000gq/T/ipykernel_17878/2982466024.py:225: VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray.\n",
-      "  waveforms = np.array(waveforms)[selection_indexes]\n",
-      "/var/folders/_g/3q5q8_dj0ydcpktxlwxb5vrh0000gq/T/ipykernel_17878/2982466024.py:232: UserWarning: To copy construct from a tensor, it is recommended to use sourceTensor.clone().detach() or sourceTensor.clone().detach().requires_grad_(True), rather than torch.tensor(sourceTensor).\n",
-      "  waveforms = [torch.tensor(waveform) for waveform in waveforms]\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Starting plotting 3 waveforms\n",
-      "Fetching topography\n",
-      "Plotting topo\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/Users/anovosel/miniconda3/envs/phasehunter/lib/python3.11/site-packages/bmi_topography/api_key.py:49: UserWarning: You are using a demo key to fetch data from OpenTopography, functionality will be limited. See https://bmi-topography.readthedocs.io/en/latest/#api-key for more information.\n",
-      "  warnings.warn(\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Plotting waveform 1/3\n",
-      "Station 36.11758, -117.85486 has P velocity 4.96342368856812 and S velocity 3.0001093626503503\n",
-      "Plotting waveform 2/3\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/var/folders/_g/3q5q8_dj0ydcpktxlwxb5vrh0000gq/T/ipykernel_17878/2982466024.py:302: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
-      "  output_picks = output_picks.append(pd.DataFrame({'station_name': [names[i]], 'starttime' : [str(t0s[i])],\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Station 35.98249, -117.80885 has P velocity 4.229153346955616 and S velocity 2.3118595983254937\n",
-      "Plotting waveform 3/3\n",
-      "Station 35.69235, -117.75051 has P velocity 2.9537452996413585 and S velocity 1.3863453902284213\n",
-      "Plotting stations\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/var/folders/_g/3q5q8_dj0ydcpktxlwxb5vrh0000gq/T/ipykernel_17878/2982466024.py:302: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
-      "  output_picks = output_picks.append(pd.DataFrame({'station_name': [names[i]], 'starttime' : [str(t0s[i])],\n",
-      "/var/folders/_g/3q5q8_dj0ydcpktxlwxb5vrh0000gq/T/ipykernel_17878/2982466024.py:302: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
-      "  output_picks = output_picks.append(pd.DataFrame({'station_name': [names[i]], 'starttime' : [str(t0s[i])],\n"
-     ]
     }
    ],
    "source": [
@@ -514,7 +385,16 @@
     "\n",
     "with gr.Blocks() as demo:\n",
     "    gr.HTML(\"\"\"<h1>PhaseHunter</h1>\n",
-    "<p>This app allows one to detect <mark style=\"background-color: red; color: white;\">P</mark> and <mark style=\"background-color: blue; color: white;\">S</mark> seismic phases along with <span style=\"background-image: linear-gradient(to right, #f12711, #f5af19); \n",
+    "<p>This app allows uses a new neural network called PhaseHunter to detect <span style=\"background-image: linear-gradient(to right, #ED213A, #93291E); \n",
+    "               -webkit-background-clip: text;\n",
+    "               -webkit-text-fill-color: transparent;\n",
+    "               background-clip: text;\n",
+    "               font-size: 24px;\">P</span> and \n",
+    "               <span style=\"background-image: linear-gradient(to right, #00B4DB, #0083B0); \n",
+    "               -webkit-background-clip: text;\n",
+    "               -webkit-text-fill-color: transparent;\n",
+    "               background-clip: text;\n",
+    "               font-size: 24px;\">S</span> seismic phases along with <span style=\"background-image: linear-gradient(to right, #f12711, #f5af19); \n",
     "               -webkit-background-clip: text;\n",
     "               -webkit-text-fill-color: transparent;\n",
     "               background-clip: text;\n",
@@ -527,8 +407,9 @@
     "  <li>By selecting an earthquake from the global earthquake catalogue.</li>\n",
     "</ol>\n",
     "<p>Please upload your waveform in <code>.npy</code> (numpy) format.</p>\n",
-    "<p>Your waveform should be sampled at 100 samples per second and have 3 (Z, N, E) or 1 (Z) channels. If your file is longer than 60 seconds, the app will only use the first 60 seconds of the waveform.</p>\n",
-    "            \"\"\")\n",
+    "<p>Your waveform should be sampled at 100 samples per second and have 3 (Z, N, E) or 1 (Z) channels. \n",
+    "If your file is longer than 60 seconds, the app will only use the first 60 seconds of the waveform.</p>\n",
+    "\"\"\")\n",
     "    with gr.Tab(\"Try on a single station\"):\n",
     "        with gr.Row(): \n",
     "            # Define the input and output types for Gradio\n",

app.py

@@ -347,7 +347,16 @@ model.eval()
 
 with gr.Blocks() as demo:
     gr.HTML("""<h1>PhaseHunter</h1>
-<p>This app allows one to detect <mark style="background-color: red; color: white;">P</mark> and <mark style="background-color: blue; color: white;">S</mark> seismic phases along with <span style="background-image: linear-gradient(to right, #f12711, #f5af19); 
+<p>This app allows uses a new neural network called PhaseHunter to detect <span style="background-image: linear-gradient(to right, #ED213A, #93291E); 
+               -webkit-background-clip: text;
+               -webkit-text-fill-color: transparent;
+               background-clip: text;
+               font-size: 24px;">P</span> and 
+               <span style="background-image: linear-gradient(to right, #00B4DB, #0083B0); 
+               -webkit-background-clip: text;
+               -webkit-text-fill-color: transparent;
+               background-clip: text;
+               font-size: 24px;">S</span> seismic phases along with <span style="background-image: linear-gradient(to right, #f12711, #f5af19); 
                -webkit-background-clip: text;
                -webkit-text-fill-color: transparent;
                background-clip: text;
@@ -360,8 +369,9 @@ with gr.Blocks() as demo:
   <li>By selecting an earthquake from the global earthquake catalogue.</li>
 </ol>
 <p>Please upload your waveform in <code>.npy</code> (numpy) format.</p>
-<p>Your waveform should be sampled at 100 samples per second and have 3 (Z, N, E) or 1 (Z) channels. If your file is longer than 60 seconds, the app will only use the first 60 seconds of the waveform.</p>
-            """)
+<p>Your waveform should be sampled at 100 samples per second and have 3 (Z, N, E) or 1 (Z) channels. 
+If your file is longer than 60 seconds, the app will only use the first 60 seconds of the waveform.</p>
+""")
     with gr.Tab("Try on a single station"):
         with gr.Row(): 
             # Define the input and output types for Gradio