used uuid as the animation file

app.py

@@ -1,6 +1,7 @@
 
 import os
 import csv
+import uuid
 import json
 import torch
 import requests
@@ -18,7 +19,6 @@ from funcs.processor import process_data
 from funcs.plot_func import plot_sensor_data_from_json
 from funcs.dataloader import BaseDataset2, read_json_files
 
-
 DEVICE = torch.device("cpu")
 reducer10d = PHATEAE(epochs=30, n_components=10, lr=.0001, batch_size=128, t='auto', knn=8, relax=True, metric='euclidean')
 reducer10d.load('models/r10d_3.pth')
@@ -176,7 +176,6 @@ def scores_to_dataframe(scores, start_time='2022-07-01 09:15:00+05:30', start_sc
     return df
 
 def get_som_mp4_v2(csv_file_box, slice_size_slider, sample_rate, window_size_slider, reducer=reducer10d, cluster=cluster_som):
-    os.remove('animation.mp4')
     processed_file_box, json_file_box, slices_per_leg, plot_box_leg, plot_box_overlay, slice_slider, plot_slice_leg, get_all_slice, slice_json_box, time_list = process_data(csv_file_box, 
                                                                                                                                                                   slice_size_slider, 
                                                                                                                                                                   sample_rate, 
@@ -226,7 +225,9 @@ def get_som_mp4_v2(csv_file_box, slice_size_slider, sample_rate, window_size_sli
         csv_writer.writerow(header)
         csv_writer.writerows(processed_data)
     
-    os.system('curl -X POST -F "csv_file=@animation_table.csv" https://metric-space.ngrok.io/generate --output animation.mp4')
+    name_animation_file = f'animation-{str(uuid.uuid4())}.mp4'
+
+    os.system('curl -X POST -F "csv_file=@animation_table.csv" https://metric-space.ngrok.io/generate --output name_animation_file')
     # #with hhtp requests
     # url = "https://metric-space.ngrok.io/generate"
     # file = {'csv_file': open('animation_table.csv', 'rb')}
@@ -245,7 +246,7 @@ def get_som_mp4_v2(csv_file_box, slice_size_slider, sample_rate, window_size_sli
 
     # return processed_file_box, json_file_box, slices_per_leg, plot_box_leg, plot_box_overlay, slice_slider, plot_slice_leg, get_all_slice, slice_json_box, som_video, 'animation.mp4', fig
         
-    return processed_file_box, json_file_box, slices_per_leg, plot_box_leg, plot_box_overlay, slice_slider, plot_slice_leg, get_all_slice, slice_json_box, 'som_sequence.mp4', 'animation.mp4', fig
+    return processed_file_box, json_file_box, slices_per_leg, plot_box_leg, plot_box_overlay, slice_slider, plot_slice_leg, get_all_slice, slice_json_box, 'som_sequence.mp4', name_animation_file, fig
     return processed_file_box, json_file_box, slices_per_leg, plot_box_leg, plot_box_overlay, slice_slider, plot_slice_leg, get_all_slice, slice_json_box, 'som_sequence.mp4', None
 
 # ml inference