new changes to run streamlit

autotab_app final.py

@@ -1,118 +0,0 @@
-import os
-import streamlit as st
-import autotab.TabPrediction as tp
-import pandas as pd
-import numpy as np 
-from autotab.TabDataReprGen import TabDataReprGen
-from PIL import Image
-
-st.set_page_config(
-    page_title="AutoTab tab generator",
-    layout="centered", # centered
-    initial_sidebar_state="auto") # collapsed
-
-image_path = "https://images.unsplash.com/photo-1535587566541-97121a128dc5?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=870&q=80"
-st.write(f'<div class="banner" style="background-image: linear-gradient(rgba(0,0,0,0.4),rgba(0,0,0,0.4)), url({image_path});"><h1>Autotab</h1><p>Learning the guitar the easy way</p></div>', unsafe_allow_html=True)
-CSS = """
-.banner {
-    background-position: center;
-    background-repeat: no-repeat;
-    background-size: cover;
-    position: relative;
-    height: 300px;
-    text-align: center;
-    margin-top: -100px;
-    margin-left: -480px;
-    margin-right: -480px;
-}
-.banner h1 {
-    padding-top: 120px;
-    margin: 0;
-    color: white;
-    text-shadow: 1px 1px 3px rgba(0,0,0,0.2);
-    font-size: 56px;
-    font-weight: bold;
-}
-.banner p {
-    font-size: 32px;
-    color: white;
-    opacity: .7;
-    text-shadow: 1px 1px 3px rgba(0,0,0,0.2);
-}
-"""
-st.write(f'<style>{CSS}</style>', unsafe_allow_html=True)
-
-
-st.set_option('deprecation.showfileUploaderEncoding', False)
-
-uploaded_file = st.file_uploader("choose a music file:", type="wav")
-
-processed_file = None
-
-mode = st.radio('Choose Mode of Tab production:', ('Ergonomic Simple', 'Ergonomic Rhythm', 'All Frames'))
-st.write('<style>div.row-widget.stRadio > div{flex-direction:row;}</style>', unsafe_allow_html=True)
-
-###########################################################
-# slider for number of divisions 
-
-num_div = st.slider('Select number of frets per line', 1, 10, 3)
-# web_tabs(tabs, num_div=4, len_div=16)
-
-###########################################################
-
-model = tp.load_model_and_weights()
-model.load_weights('./h5-model/full_val0_75acc_weights.h5')
-genrep = TabDataReprGen()
-
-if uploaded_file is not None:
-    x_new = genrep.load_rep_from_raw_file(uploaded_file)
-    y_pred = model.predict(x_new)
-    processed_file= uploaded_file
-    
-if uploaded_file is not None and mode == 'Ergonomic Simple': 
-    st.title("""
-            Ergonomic Simple predicted Tabs: 
-    """)
-    if uploaded_file != processed_file:        
-        x_new = genrep.load_rep_from_raw_file(uploaded_file)
-        # st.write(x_new.shape)
-        y_pred = model.predict(x_new)
-        processed_file = uploaded_file
-    
-    all_frames_tab = tp.make_smart_tab(y_pred, len(y_pred))
-    simple_tabs = tp.make_squeezed_tab(all_frames_tab)
-    simple_text = tp.web_tabs(simple_tabs)
-    st.text(simple_text)
-    
-if uploaded_file is not None and mode == 'Ergonomic Rhythm': 
-    st.title("""
-            Ergonomic Rhythm predicted Tabs:
-    """)
-    if uploaded_file != processed_file:        
-        x_new = genrep.load_rep_from_raw_file(uploaded_file)
-        # st.write(x_new.shape)
-        y_pred = model.predict(x_new)
-        processed_file = uploaded_file
-    
-    all_frames_tab = tp.make_smart_tab(y_pred, len(y_pred))
-    rythm_tabs = tp.make_dynamic_tab(all_frames_tab)
-    rythm_text = tp.web_tabs(rythm_tabs)
-    st.text(rythm_text)
-    
-if uploaded_file is not None and mode == 'All Frames': 
-    st.title("""
-            All Frames predicted Tabs:
-    """)
-    if uploaded_file != processed_file:        
-        x_new = genrep.load_rep_from_raw_file(uploaded_file)
-        # st.write(x_new.shape)
-        y_pred = model.predict(x_new)
-        processed_file = uploaded_file
-    
-
-    all_frames_tab = tp.make_smart_tab(y_pred, len(y_pred))
-    ################################################
-    # all_frames_tab.to_csv('all_frames_tab.csv')
-    ################################################
-    all_frames_text = tp.web_tabs(all_frames_tab)
-    st.text(all_frames_text)

streamlit/autotab_app final.py

@@ -1,118 +0,0 @@
-import os
-import streamlit as st
-import autotab.TabPrediction as tp
-import pandas as pd
-import numpy as np 
-from autotab.TabDataReprGen import TabDataReprGen
-from PIL import Image
-
-st.set_page_config(
-    page_title="AutoTab tab generator",
-    layout="centered", # centered
-    initial_sidebar_state="auto") # collapsed
-
-image_path = "https://images.unsplash.com/photo-1535587566541-97121a128dc5?ixlib=rb-1.2.1&ixid=MnwxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8&auto=format&fit=crop&w=870&q=80"
-st.write(f'<div class="banner" style="background-image: linear-gradient(rgba(0,0,0,0.4),rgba(0,0,0,0.4)), url({image_path});"><h1>Autotab</h1><p>Learning the guitar the easy way</p></div>', unsafe_allow_html=True)
-CSS = """
-.banner {
-    background-position: center;
-    background-repeat: no-repeat;
-    background-size: cover;
-    position: relative;
-    height: 300px;
-    text-align: center;
-    margin-top: -100px;
-    margin-left: -480px;
-    margin-right: -480px;
-}
-.banner h1 {
-    padding-top: 120px;
-    margin: 0;
-    color: white;
-    text-shadow: 1px 1px 3px rgba(0,0,0,0.2);
-    font-size: 56px;
-    font-weight: bold;
-}
-.banner p {
-    font-size: 32px;
-    color: white;
-    opacity: .7;
-    text-shadow: 1px 1px 3px rgba(0,0,0,0.2);
-}
-"""
-st.write(f'<style>{CSS}</style>', unsafe_allow_html=True)
-
-
-st.set_option('deprecation.showfileUploaderEncoding', False)
-
-uploaded_file = st.file_uploader("choose a music file:", type="wav")
-
-processed_file = None
-
-mode = st.radio('Choose Mode of Tab production:', ('Ergonomic Simple', 'Ergonomic Rhythm', 'All Frames'))
-st.write('<style>div.row-widget.stRadio > div{flex-direction:row;}</style>', unsafe_allow_html=True)
-
-###########################################################
-# slider for number of divisions 
-
-num_div = st.slider('Select number of frets per line', 1, 10, 3)
-# web_tabs(tabs, num_div=4, len_div=16)
-
-###########################################################
-
-model = tp.load_model_and_weights()
-model.load_weights('./h5-model/full_val0_75acc_weights.h5')
-genrep = TabDataReprGen()
-
-if uploaded_file is not None:
-    x_new = genrep.load_rep_from_raw_file(uploaded_file)
-    y_pred = model.predict(x_new)
-    processed_file= uploaded_file
-    
-if uploaded_file is not None and mode == 'Ergonomic Simple': 
-    st.title("""
-            Ergonomic Simple predicted Tabs: 
-    """)
-    if uploaded_file != processed_file:        
-        x_new = genrep.load_rep_from_raw_file(uploaded_file)
-        # st.write(x_new.shape)
-        y_pred = model.predict(x_new)
-        processed_file = uploaded_file
-    
-    all_frames_tab = tp.make_smart_tab(y_pred, len(y_pred))
-    simple_tabs = tp.make_squeezed_tab(all_frames_tab)
-    simple_text = tp.web_tabs(simple_tabs)
-    st.text(simple_text)
-    
-if uploaded_file is not None and mode == 'Ergonomic Rhythm': 
-    st.title("""
-            Ergonomic Rhythm predicted Tabs:
-    """)
-    if uploaded_file != processed_file:        
-        x_new = genrep.load_rep_from_raw_file(uploaded_file)
-        # st.write(x_new.shape)
-        y_pred = model.predict(x_new)
-        processed_file = uploaded_file
-    
-    all_frames_tab = tp.make_smart_tab(y_pred, len(y_pred))
-    rythm_tabs = tp.make_dynamic_tab(all_frames_tab)
-    rythm_text = tp.web_tabs(rythm_tabs)
-    st.text(rythm_text)
-    
-if uploaded_file is not None and mode == 'All Frames': 
-    st.title("""
-            All Frames predicted Tabs:
-    """)
-    if uploaded_file != processed_file:        
-        x_new = genrep.load_rep_from_raw_file(uploaded_file)
-        # st.write(x_new.shape)
-        y_pred = model.predict(x_new)
-        processed_file = uploaded_file
-    
-
-    all_frames_tab = tp.make_smart_tab(y_pred, len(y_pred))
-    ################################################
-    # all_frames_tab.to_csv('all_frames_tab.csv')
-    ################################################
-    all_frames_text = tp.web_tabs(all_frames_tab)
-    st.text(all_frames_text)

streamlit/autotab_app.py

@@ -2,7 +2,7 @@ import os
 import streamlit as st
 import autotab.TabPrediction as tp
 import pandas as pd
-import numpy as np 
+import numpy as np
 from autotab.TabDataReprGen import TabDataReprGen
 from PIL import Image
 
@@ -70,42 +70,42 @@ if uploaded_file is not None:
     x_new = genrep.load_rep_from_raw_file(uploaded_file)
     y_pred = model.predict(x_new)
     processed_file= uploaded_file
-    
-if uploaded_file is not None and mode == 'Ergonomic Simple': 
+
+if uploaded_file is not None and mode == 'Ergonomic Simple':
     st.title("""
-            Ergonomic Simple predicted Tabs: 
+            Ergonomic Simple predicted Tabs:
     """)
-    if uploaded_file != processed_file:        
+    if uploaded_file != processed_file:
         x_new = genrep.load_rep_from_raw_file(uploaded_file)
         # st.write(x_new.shape)
         y_pred = model.predict(x_new)
         processed_file = uploaded_file
-    
+
     all_frames_tab = tp.make_smart_tab(y_pred, len(y_pred))
     simple_tabs = tp.make_squeezed_tab(all_frames_tab)
     simple_text = tp.web_tabs(simple_tabs)
     st.text(simple_text)
-    
-if uploaded_file is not None and mode == 'Ergonomic Rhythm': 
+
+if uploaded_file is not None and mode == 'Ergonomic Rhythm':
     st.title("""
             Ergonomic Rhythm predicted Tabs:
     """)
-    if uploaded_file != processed_file:        
+    if uploaded_file != processed_file:
         x_new = genrep.load_rep_from_raw_file(uploaded_file)
         # st.write(x_new.shape)
         y_pred = model.predict(x_new)
         processed_file = uploaded_file
-    
+
     all_frames_tab = tp.make_smart_tab(y_pred, len(y_pred))
     rythm_tabs = tp.make_dynamic_tab(all_frames_tab)
     rythm_text = tp.web_tabs(rythm_tabs)
     st.text(rythm_text)
-    
-if uploaded_file is not None and mode == 'All Frames': 
+
+if uploaded_file is not None and mode == 'All Frames':
     st.title("""
             All Frames predicted Tabs:
     """)
-    if uploaded_file != processed_file:        
+    if uploaded_file != processed_file:
         x_new = genrep.load_rep_from_raw_file(uploaded_file)
         # st.write(x_new.shape)
         y_pred = model.predict(x_new)

streamlit/autotab_app_hoz.py

@@ -5,6 +5,15 @@ import pandas as pd
 import numpy as np
 from autotab.TabDataReprGen import TabDataReprGen
 from PIL import Image
+import sys
+
+
+# Insert the parent directory into sys.path
+sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
+
+# Now you can import from autotab
+import autotab.TabPrediction as tp
+
 
 st.set_page_config(
     page_title="AutoTab tab generator",