tensorflow: publish desktop variant

plugins/tensorflow-lite/src/predict/__init__.py

@@ -5,7 +5,6 @@ from PIL import Image
 import re
 import scrypted_sdk
 from typing import Any, List, Tuple, Mapping
-from gi.repository import Gst
 import asyncio
 import time
 import sys
@@ -16,6 +15,11 @@ from collections import namedtuple
 from .sort_oh import tracker
 import numpy as np
 
+try:
+    from gi.repository import Gst
+except:
+    pass
+
 Rectangle = namedtuple('Rectangle', 'xmin ymin xmax ymax')
 
 def intersect_area(a: Rectangle, b: Rectangle):  # returns None if rectangles don't intersect
@@ -252,7 +256,7 @@ class PredictPlugin(DetectPlugin, scrypted_sdk.BufferConverter, scrypted_sdk.Set
         (w, h) = self.get_input_size()
         (iw, ih) = image.size
 
-        if not detection_session.tracker:
+        if detection_session and not detection_session.tracker:
             t = self.trackers.get(detection_session.id)
             if not t:
                 t = tracker.Sort_OH(scene=np.array([iw, ih]))
@@ -340,9 +344,11 @@ class PredictPlugin(DetectPlugin, scrypted_sdk.BufferConverter, scrypted_sdk.Set
      
         ret1 = self.detect_once(first, settings, src_size, cvss1)
         first.close()
-        detection_session.processed = detection_session.processed + 1
+        if detection_session:
+            detection_session.processed = detection_session.processed + 1
         ret2 = self.detect_once(second, settings, src_size, cvss2)
-        detection_session.processed = detection_session.processed + 1
+        if detection_session:
+            detection_session.processed = detection_session.processed + 1
         second.close()
 
         ret = ret1
@@ -379,7 +385,7 @@ class PredictPlugin(DetectPlugin, scrypted_sdk.BufferConverter, scrypted_sdk.Set
 
         ret['detections'] = detections
 
-        if not multipass_crop:
+        if not multipass_crop and detection_session:
             sort_input = []
             for d in ret['detections']:
                 r: ObjectDetectionResult = d