add app

app.py

@@ -0,0 +1,62 @@
+import sys
+sys.path.append('src/') # Add src to path
+
+import gradio as gr
+
+from utils import get_array, save_video, make_predictions
+from data.processing import Scaler
+
+examples = [["data/2023-05-05.mp4", '2023-05-05', '12:00:00', '21:30:00'],
+            ["data/2023-09-07.mp4", '2023-09-07', '07:00:00', '16:30:00'],
+            ["data/2023-10-28.mp4", '2023-10-28', '12:00:00', '21:30:00'],
+            ["data/2023-11-09.mp4", '2023-11-09', '01:30:00', '11:00:00'],
+            ["data/2023-11-13.mp4", '2023-11-15', '00:00:00', '09:30:00'],
+            ["data/2023-11-18.mp4", '2023-11-18', '00:00:00', '09:30:00']]
+
+scaler_dict = {"2023-05-05.mp4": "models/scaler_1.pkl",
+               "2023-09-07.mp4": "models/scaler_2.pkl",
+               "2023-10-28.mp4": "models/scaler_3.pkl",
+               "2023-11-09.mp4": "models/scaler_4.pkl",
+               "2023-11-13.mp4": "models/scaler_5.pkl",
+               "2023-11-18.mp4": "models/scaler_6.pkl"}
+
+def predict(source, date, start, end):
+
+    print(f"Date: {date}")
+    print(f"Start: {start}")
+    print(f"End: {end}")
+
+    X, y = get_array(source, scaler_dict)
+    print(X.shape, y.shape)
+
+    file_path_input = 'data/input.mp4'
+    save_video(X, threshold=0, file_path=file_path_input)
+    
+    file_path_output = 'data/output.mp4'
+    save_video(y, threshold=0, file_path=file_path_output)
+
+    ypred = make_predictions(X)
+
+    file_path_predict = 'data/predict.mp4'
+    save_video(ypred, threshold=0.1, file_path=file_path_predict)
+
+    return [file_path_input, file_path_output, file_path_predict]
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=[
+        gr.Video(label="Source", visible=False),
+        gr.Text(label='Date'),
+        gr.Text(label='Start'),
+        gr.Text(label='End')
+        ],
+    outputs=[
+        gr.Video(label='Input'),
+        gr.Video(label='Output'),
+        gr.Video(label='Prediction')
+    ],
+    examples=examples
+)
+
+if __name__ == "__main__":
+    demo.launch()