updated detection code, changed detectron2 classes to 2 in prediciton

Author: e-candeloro

source/2_training.ipynb

@@ -128,21 +128,7 @@
    "execution_count": 5,
    "id": "4122d05f-8153-4dde-9abf-362b8311217b",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Skip loading parameter 'roi_heads.box_predictor.cls_score.weight' to the model due to incompatible shapes: (3, 1024) in the checkpoint but (2, 1024) in the model! You might want to double check if this is expected.\n",
-      "Skip loading parameter 'roi_heads.box_predictor.cls_score.bias' to the model due to incompatible shapes: (3,) in the checkpoint but (2,) in the model! You might want to double check if this is expected.\n",
-      "Skip loading parameter 'roi_heads.box_predictor.bbox_pred.weight' to the model due to incompatible shapes: (8, 1024) in the checkpoint but (4, 1024) in the model! You might want to double check if this is expected.\n",
-      "Skip loading parameter 'roi_heads.box_predictor.bbox_pred.bias' to the model due to incompatible shapes: (8,) in the checkpoint but (4,) in the model! You might want to double check if this is expected.\n",
-      "Some model parameters or buffers are not found in the checkpoint:\n",
-      "\u001b[34mroi_heads.box_predictor.bbox_pred.{bias, weight}\u001b[0m\n",
-      "\u001b[34mroi_heads.box_predictor.cls_score.{bias, weight}\u001b[0m\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "model = Detectron2DetectionPredictor(\n",
     "    output_dir=output_path,\n",
@@ -227,7 +213,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "id": "c9f7e6e3-5bb5-4dd7-a9d4-7097700691de",
    "metadata": {
     "tags": []
@@ -272,7 +258,7 @@
     "    ratio = spacing/spacing_min\n",
     "    with WholeSlideImage(image_path) as wsi:\n",
     "        spacing = wsi.get_real_spacing(spacing_min)\n",
-    "        print(f\"Spacing: {spacing}\\nSpacing const: {SPACING_CONST}\")\n",
+    "        print(f\"Spacing: {spacing} - Spacing const: {SPACING_CONST} - ratio: {ratio}\")\n",
     "\n",
     "\n",
     "    for x_batch, y_batch, info in tqdm(iterator):\n",
@@ -393,7 +379,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "id": "7bf43390-c419-4b8a-9f5a-104cb8040592",
    "metadata": {},
    "outputs": [
@@ -402,8 +388,7 @@
      "output_type": "stream",
      "text": [
       "predicting...\n",
-      "Spacing: 0.24199951445730394\n",
-      "Spacing const: 0.24199951445730394\n"
+      "Spacing: 0.24199951445730394 - Spacing const: 0.24199951445730394 - ratio: 2.0\n"
      ]
     },
     {
@@ -421,14 +406,14 @@
       "  max_size = (max_size + (stride - 1)) // stride * stride\n",
       "/venv/lib/python3.8/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at  ../aten/src/ATen/native/TensorShape.cpp:2157.)\n",
       "  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]\n",
-      "100%|██████████| 379/379 [00:44<00:00,  8.43it/s]\n"
+      "100%|██████████| 379/379 [00:42<00:00,  8.95it/s]\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Predicted 30007 points\n",
+      "Predicted 14925 points\n",
       "saving predictions...\n",
       "finished!\n"
      ]

source/3_inference.ipynb

@@ -56,7 +56,7 @@ def __init__(self, output_dir, threshold, nms_threshold, weight_root):
         cfg.DATALOADER.NUM_WORKERS = 1
 
         cfg.MODEL.ROI_HEADS.BATCH_SIZE_PER_IMAGE = 512
-        cfg.MODEL.ROI_HEADS.NUM_CLASSES = 1
+        cfg.MODEL.ROI_HEADS.NUM_CLASSES = 2 #was 1!
         cfg.MODEL.ANCHOR_GENERATOR.SIZES = [[16, 24, 32]]
 
         cfg.SOLVER.IMS_PER_BATCH = 10