adding test Script for data generation and fixing stack trace error (#…

…800)

client/src/use/useTrackStore.ts

@@ -62,9 +62,10 @@ export default function useTrackStore({ markChangesPending }: UseTrackStoreParam
   }
 
   function getNewTrackId() {
-    return trackIds.value.length
-      ? Math.max(...trackIds.value) + 1
-      : 0;
+    if (trackIds.value.length) {
+      return trackIds.value.reduce((prev, current) => Math.max(prev, current)) + 1;
+    }
+    return 0;
   }
 
   function onChange(

testutils/scripts/generateLargeDataset.py

@@ -0,0 +1,74 @@
+import argparse
+import json
+import os
+from PIL import Image
+from tqdm import tqdm
+import random
+
+def create_track_json(directory,image_count, track_count, type_count=10, max_track_length=1,):
+    """
+    Read in JSON file and video file and extract bounds and create files for all the other data
+    """
+    types = []
+    for type in range(type_count):
+        types.append(f'Type_{type}')
+    tracks = {}
+    for track in tqdm(range(track_count)):
+
+        track_obj ={
+            'trackId': track,
+            'begin': float('inf'),
+            'end': float('-inf'),
+            'confidencePairs': [[types[random.randint(0, type_count-1)], random.randint(0,100)/100.0]],
+            'features': []
+        }
+        start_frame = random.randint(0, image_count-1)
+        adjusted_max_track_length = max_track_length
+        if image_count - start_frame < max_track_length:
+            adjusted_max_track_length = image_count - start_frame
+        if (adjusted_max_track_length > 1):
+            track_length = random.randint(1, adjusted_max_track_length)
+        else:
+            track_length = adjusted_max_track_length
+        for frame in range(track_length):
+            frame = start_frame + frame
+            feature = {
+                'frame': frame,
+                'keyframe': True,
+                'bounds': [0,0,1,1],
+            }
+            track_obj['begin'] = min(track_obj['begin'], frame)
+            track_obj['end'] = max(track_obj['end'], frame)
+            track_obj["features"].append(feature)
+        tracks[track] = track_obj
+    json_file = f"{directory}/result_test.json"
+    with open(json_file, 'w') as outfile:
+        json.dump(tracks, outfile)
+
+def create_images(directory, number):
+    # Create a folder to hold it
+    os.mkdir(directory)
+    for index in tqdm(range(number)):
+        img = Image.new("RGB", (1, 1))
+        img.save(f'{directory}/image_{index}.jpg')
+
+def main(args):
+    create_images(args.directory, int(args.images))
+    create_track_json(args.directory, int(args.images), int(args.tracks), int(args.types), int(args.track_length))
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(description='Create Large Dataset')
+
+    parser.add_argument('--images', default=100, help='Number of Images')
+    parser.add_argument('--tracks', default=100, help='Number of Tracks')
+    parser.add_argument('--types', default=10, help='Number of Types')
+    parser.add_argument('--track_length', default=1, help='Max Track Length')
+    parser.add_argument('--directory', default="./dataset", help='outputDirectory')
+
+    return parser.parse_args()
+
+
+if __name__ == '__main__':
+    args = parse_args()
+    main(args)