[AZ-180] Enhance setup and improve inference logging

- Added a new Cython extension for the engine factory to the setup configuration.
- Updated the inference module to include additional logging for video batch processing and annotation callbacks.
- Refactored test cases to standardize the detection endpoint responses and include channel IDs in headers for better event handling.

src/inference.pyx

@@ -268,14 +268,24 @@ cdef class Inference:
                 batch_count += 1
                 tf = total_frames if total_frames > 0 else max(frame_count, 1)
                 constants_inf.log(<str>f'Video batch {batch_count}: frame {frame_count}/{tf} ({frame_count*100//tf}%)')
+                last_ts = batch_timestamps[len(batch_timestamps) - 1] if batch_timestamps else 0
                 self._process_video_batch(ai_config, batch_frames, batch_timestamps, original_media_name, frame_count, tf, model_w)
+                if self._annotation_callback is not None:
+                    pann = Annotation(original_media_name, original_media_name, last_ts, [])
+                    cb = self._annotation_callback
+                    cb(pann, int(frame_count * 100 / tf))
                 batch_frames = []
                 batch_timestamps = []
         if batch_frames:
             batch_count += 1
             tf = total_frames if total_frames > 0 else max(frame_count, 1)
             constants_inf.log(<str>f'Video batch {batch_count} (flush): {len(batch_frames)} remaining frames')
+            last_ts = batch_timestamps[len(batch_timestamps) - 1] if batch_timestamps else 0
             self._process_video_batch(ai_config, batch_frames, batch_timestamps, original_media_name, frame_count, tf, model_w)
+            if self._annotation_callback is not None:
+                pann = Annotation(original_media_name, original_media_name, last_ts, [])
+                cb = self._annotation_callback
+                cb(pann, 100)
         constants_inf.log(<str>f'Video done: {frame_count} frames read, {batch_count} batches processed')
         self.send_detection_status()