cleanup demos

demo/calculator.py

@@ -21,5 +21,6 @@ iface = gr.Interface(calculator,
         [0, "subtract", 1.2],
     ]
 )
+
 if __name__ == "__main__":
-    iface.launch()
+    iface.launch()

demo/diff_texts.py

@@ -11,7 +11,7 @@ def diff_texts(text1, text2):
     ]
 
 
-io = gr.Interface(
+iface = gr.Interface(
     diff_texts,
     [
         gr.inputs.Textbox(lines=3, default="The quick brown fox jumped over the lazy dogs."),
@@ -23,7 +23,7 @@ io = gr.Interface(
         " ": "none",
     }))
 
-io.test_launch()
+iface.test_launch()
 
 if __name__ == "__main__":
     io.launch()

demo/digit_classifier.py

@@ -15,7 +15,7 @@ def recognize_digit(image):
     return {str(i): prediction[i] for i in range(10)}
 
 
-io = gr.Interface(
+iface = gr.Interface(
     recognize_digit, 
     "sketchpad", 
     gradio.outputs.Label(num_top_classes=3),
@@ -23,5 +23,8 @@ io = gr.Interface(
     capture_session=True,
 )
 
-io.test_launch()
-io.launch()
+iface.test_launch()
+
+if __name__ == "__main__":
+    iface.launch()
+

demo/face_segment.py

@@ -34,5 +34,6 @@ def segment_face(inp):
 
 
 iface = gr.Interface(segment_face, "webcam", "image", capture_session=True)
+
 if __name__ == "__main__":
     iface.launch()

demo/filter_records.py

@@ -7,7 +7,7 @@ import random
 def filter_records(records, gender):
     return records[records['gender'] == gender]
 
-io = gr.Interface(filter_records,
+iface = gr.Interface(filter_records,
   [
     gr.inputs.Dataframe(headers=["name", "age", "gender"], datatype=["str", "number", "str"], row_count=5), 
     gr.inputs.Dropdown(["M", "F", "O"])
@@ -16,5 +16,8 @@ io = gr.Interface(filter_records,
   description="Enter gender as 'M', 'F', or 'O' for other."
 )
 
-io.test_launch()
-io.launch()
+iface.test_launch()
+
+if __name__ == "__main__":
+    iface.launch()
+

demo/form_graph.py

@@ -22,7 +22,7 @@ def plot_forecast(final_year, companies, noise, show_legend, point_style):
     return fig
 
 
-gr.Interface(plot_forecast,
+iface = gr.Interface(plot_forecast,
              [
                  gr.inputs.Radio([2025, 2030, 2035, 2040],
                                  label="Project to:"),
@@ -33,4 +33,7 @@ gr.Interface(plot_forecast,
                  gr.inputs.Dropdown(["cross", "line", "circle"], label="Style"),
              ],
              gr.outputs.Image(plot=True, label="forecast") 
-             ).launch()
+             )
+
+if __name__ == "__main__":
+    iface.launch()

demo/generate_tone.py

@@ -16,7 +16,7 @@ def generate_tone(note, octave, duration):
     return sr, audio
 
 
-io = gr.Interface(
+iface = gr.Interface(
     generate_tone, 
     [
         gr.inputs.Dropdown(notes, type="index"),
@@ -24,5 +24,6 @@ io = gr.Interface(
         gr.inputs.Textbox(type="number", default=1, label="Duration in seconds")
     ], "audio")
 
-io.test_launch()
-io.launch()
+iface.test_launch()
+if __name__ == "__main__":
+    iface.launch()

demo/image_classifier.py

@@ -8,9 +8,11 @@ from PIL import Image
 import requests
 from urllib.request import urlretrieve
 import json
+import os
 
 # Load human-readable labels for ImageNet.
-with open("files/imagenet_labels.json") as labels_file:
+current_dir = os.path.dirname(os.path.realpath(__file__))
+with open(os.path.join(current_dir, "files/imagenet_labels.json")) as labels_file:
     labels = json.load(labels_file)
 
 mobile_net = tf.keras.applications.MobileNetV2()
@@ -26,7 +28,7 @@ def image_classifier(im):
 image = gr.inputs.Image(shape=(224, 224))
 label = gr.outputs.Label(num_top_classes=3)
 
-io = gr.Interface(image_classifier, image, label,
+iface = gr.Interface(image_classifier, image, label,
     capture_session=True,
     interpretation="default",
     examples=[
@@ -34,4 +36,5 @@ io = gr.Interface(image_classifier, image, label,
         ["images/lion.jpg"]
     ])
 
-io.launch()
+if __name__ == "__main__":
+    iface.launch()

demo/image_mod.py

@@ -7,7 +7,7 @@ def image_mod(image):
     return image.rotate(45)
 
 
-io = gr.Interface(image_mod, 
+iface = gr.Interface(image_mod, 
              gr.inputs.Image(type="pil"), 
              "image", 
              examples=[
@@ -16,7 +16,7 @@ io = gr.Interface(image_mod,
                  ["images/lion.jpg"],
              ])
 
-io.test_launch()
+iface.test_launch()
 
 if __name__ == "__main__":
-    io.launch()
+    iface.launch()

demo/longest_word.py

@@ -9,10 +9,10 @@ def longest_word(text):
 
 ex = "The quick brown fox jumped over the lazy dog."
 
-io = gr.Interface(longest_word, "textbox", "label",
+iface = gr.Interface(longest_word, "textbox", "label",
                   interpretation="default", examples=[[ex]])
 
-io.test_launch()
+iface.test_launch()
 
 if __name__ == "__main__":
-    io.launch()
+    iface.launch()

demo/main_note.py

@@ -37,7 +37,7 @@ def main_note(audio):
         volume_per_pitch[pitch] += 1.0 * volume / total_volume
     return volume_per_pitch
 
-io = gr.Interface(
+iface = gr.Interface(
     main_note, 
     "microphone", 
     gr.outputs.Label(num_top_classes=4),
@@ -47,4 +47,5 @@ io = gr.Interface(
     ],
     interpretation="default")
 
-io.launch()
+if __name__ == "__main__":
+    iface.launch()

demo/matrix_transpose.py

@@ -7,7 +7,7 @@ def transpose(matrix):
     return matrix.T
 
 
-io = gr.Interface(
+iface = gr.Interface(
     transpose,
     gr.inputs.Dataframe(type="numpy", datatype="number", row_count=5, col_count=3),
     "numpy",
@@ -20,7 +20,7 @@ io = gr.Interface(
     ]
 )
 
-io.test_launch()
+iface.test_launch()
 
 if __name__ == "__main__":
-    io.launch()
+    iface.launch()

demo/outbreak_forecast.py

@@ -32,4 +32,4 @@ iface = gr.Interface(outbreak,
     ], 
     "plot")
 if __name__ == "__main__":
-    iface.launch()
+    iface.launch()

demo/question_answer.py

@@ -15,4 +15,4 @@ iface = gr.Interface(qa_func,
     ], 
     gr.outputs.Textbox(label="Answer"))
 if __name__ == "__main__":
-    iface.launch()
+    iface.launch()

demo/reverse_audio.py

@@ -9,7 +9,8 @@ def reverse_audio(audio):
     return (sr, np.flipud(data))
 
 
-io = gr.Interface(reverse_audio, "microphone", "audio")
+iface = gr.Interface(reverse_audio, "microphone", "audio")
 
-io.test_launch()
-io.launch()
+iface.test_launch()
+if __name__ == "__main__":
+    iface.launch()

demo/sentence_builder.py

@@ -6,7 +6,7 @@ def sentence_builder(quantity, animal, place, activity_list, morning):
     return f"""The {quantity} {animal}s went to the {place} where they {" and ".join(activity_list)} until the {"morning" if morning else "night"}"""
 
 
-io = gr.Interface(
+iface = gr.Interface(
     sentence_builder,
     [
         gr.inputs.Slider(2, 20),
@@ -23,7 +23,7 @@ io = gr.Interface(
         [8, "cat", "zoo", ["ate"], True],
     ])
 
-io.test_launch()
+iface.test_launch()
 
 if __name__ == "__main__":
-    io.launch()
+    iface.launch()

demo/sentiment_analysis.py

@@ -11,7 +11,8 @@ def sentiment_analysis(text):
     del scores["compound"]
     return scores
 
-io = gr.Interface(sentiment_analysis, "textbox", "label", interpretation="default")
+iface = gr.Interface(sentiment_analysis, "textbox", "label", interpretation="default")
 
-io.test_launch()
-io.launch()
+iface.test_launch()
+if __name__ == "__main__":
+    iface.launch()

demo/spectogram.py

@@ -15,7 +15,8 @@ def spectrogram(audio):
     return plt
 
 
-io = gr.Interface(spectrogram, "audio", "plot")
+iface = gr.Interface(spectrogram, "audio", "plot")
 
-io.test_launch()
-io.launch()
+iface.test_launch()
+if __name__ == "__main__":
+    iface.launch()

demo/stock_forecast.py

@@ -23,7 +23,7 @@ def stock_forecast(final_year, companies, noise, show_legend, point_style):
     return fig
 
 
-io = gr.Interface(
+iface = gr.Interface(
     stock_forecast,
     [
         gr.inputs.Radio([2025, 2030, 2035, 2040], label="Project to:"),
@@ -33,5 +33,6 @@ io = gr.Interface(
         gr.inputs.Dropdown(["cross", "line", "circle"], label="Style")],
     gr.outputs.Image(plot=True, label="forecast"))
 
-io.test_launch()
-io.launch()
+iface.test_launch()
+if __name__ == "__main__":
+    iface.launch()

demo/tax_calculator.py

@@ -25,7 +25,7 @@ def tax_calculator(income, marital_status, assets):
     
     return round(total_tax)
 
-io = gr.Interface(
+iface = gr.Interface(
     tax_calculator, 
     [
         "number",
@@ -44,4 +44,5 @@ io = gr.Interface(
     ]
 )
 
-io.launch()
+if __name__ == "__main__":
+    iface.launch()

demo/text_analysis.py

@@ -23,7 +23,7 @@ def text_analysis(text):
     return pos_tokens, pos_count, html
 
 
-io = gr.Interface(
+iface = gr.Interface(
     text_analysis,
     gr.inputs.Textbox(placeholder="Enter sentence here..."),
     [
@@ -35,5 +35,6 @@ io = gr.Interface(
     ]
 )
 
-io.test_launch()
-io.launch()
+iface.test_launch()
+if __name__ == "__main__":
+    iface.launch()

demo/titanic_survival.py

@@ -8,8 +8,10 @@ from sklearn import preprocessing
 from sklearn.model_selection import train_test_split
 from sklearn.ensemble import RandomForestClassifier
 from sklearn.metrics import accuracy_score
+import os
 
-data = pd.read_csv('files/titanic.csv')
+current_dir = os.path.dirname(os.path.realpath(__file__))
+data = pd.read_csv(os.path.join(current_dir, 'files/titanic.csv'))
 
 def encode_age(df):
     df.Age = df.Age.fillna(-0.5)
@@ -66,7 +68,7 @@ def predict_survival(passenger_class, is_male, age, company, fare, embark_point)
     pred = clf.predict_proba(df)[0]
     return {'Perishes': pred[0], 'Survives': pred[1]}
 
-io = gr.Interface(
+iface = gr.Interface(
     predict_survival,
     [
         gr.inputs.Dropdown(["first", "second", "third"], type="index"),
@@ -85,4 +87,5 @@ io = gr.Interface(
     interpretation="default"
 )
 
-io.launch()
+if __name__ == "__main__":
+    iface.launch()

demo/webcam.py

@@ -8,7 +8,8 @@ def snap(image):
     return np.flipud(image)
 
 
-io = gr.Interface(snap, gr.inputs.Image(shape=(100,100), image_mode="L", source="webcam"), "image")
+iface = gr.Interface(snap, gr.inputs.Image(shape=(100,100), image_mode="L", source="webcam"), "image")
 
-io.test_launch()
-io.launch()
+iface.test_launch()
+if __name__ == "__main__":
+    iface.launch()

demo/zip_to_json.py

@@ -16,7 +16,8 @@ def zip_to_json(file_obj):
     return files
 
 
-io = gr.Interface(zip_to_json, "file", "json")
+iface = gr.Interface(zip_to_json, "file", "json")
 
-io.test_launch()
-io.launch()
+iface.test_launch()
+if __name__ == "__main__":
+    iface.launch()

demo/zip_two_files.py

@@ -11,7 +11,7 @@ def zip_two_files(file1, file2):
     return "tmp.zip"
 
 
-io = gr.Interface(
+iface = gr.Interface(
     zip_two_files, 
     ["file", "file"], 
     "file",
@@ -21,5 +21,6 @@ io = gr.Interface(
     ]
 )
 
-io.test_launch()
-io.launch()
+iface.test_launch()
+if __name__ == "__main__":
+    iface.launch()