Comments

Author: mailseth

src/modules/ObjectDetectionCoral/options.py

@@ -163,7 +163,7 @@ def __init__(self):
 
         self.MAX_PIPELINE_QUEUE_LEN             = 1000      # Multi-only
         self.TILE_OVERLAP                       = 15        # Multi-only.
-        self.DOWNSAMPLE_BY                      = 5.2       # Multi-only. Smaller number results in more tiles generated
+        self.DOWNSAMPLE_BY                      = 6.0       # Multi-only. Smaller number results in more tiles generated
         self.IOU_THRESHOLD                      = 0.1       # Multi-only
 
         # ----------------------------------------------------------------------

src/modules/ObjectDetectionCoral/tpu_runner.py

@@ -90,7 +90,7 @@ def __init__(self, fname_list: list, tpu_name: str, queues: list, rebalancing_lo
 
 
     def start(self, seg_idx: int, fbytes: bytes):
-        logging.info(f"Loading into {self.tpu_name}: {self.fname_list[seg_idx]}")
+        logging.info(f"Loading {self.tpu_name}: {self.fname_list[seg_idx]}")
 
         try:
             self.interpreter = edgetpu.make_interpreter(fbytes, delegate=self.delegate)
@@ -1095,8 +1095,6 @@ def _resize_and_chop_tiles(self,
                                m_width: int,
                                m_height: int):
         """
-        Run the image resizing in an independent process pool.
-        
         Image resizing is one of the more expensive things we're doing here.
         It's expensive enough that it may take as much CPU time as inference
         under some circumstances. The Lanczos resampling kernel in particular
@@ -1148,6 +1146,7 @@ def _resize_and_chop_tiles(self,
         tiles = []
         for x_off in range(0, resamp_x - options.tile_overlap, m_width - options.tile_overlap):
             for y_off in range(0, resamp_y - options.tile_overlap, m_height - options.tile_overlap):
+                # Adjust contrast on a per-chunk basis; we will likely be quantizing the image during scaling
                 image_chunk = ImageOps.autocontrast(image.crop((x_off,
                                                                 y_off,
                                                                 x_off + m_width,
@@ -1160,6 +1159,10 @@ def _resize_and_chop_tiles(self,
 
                 tiles.append((cropped_arr.astype(self.input_details['dtype']), resamp_info))
 
+                # Check again with various scales
+                #Image.fromarray((tiles[-1][0] + 128).astype(np.uint8)).save("test.png")
+
+
         return tiles