Upload app.py

app.py

@@ -34,7 +34,10 @@ import focus_qc  # v6: grid-line focus QC before segmentation (see focus_qc.py)
 HF_REPO_ID = "LiangLabUMB/cellposecellcounter"
 HF_REPO_ID2 = "LiangLabUMB/viability_model"
 MODEL_OPTIONS = {
-    "Hemocytometer Model": "hemocytometer_retrained_20260825.npy",
+    # 26 Oct 2026: v6 weights (trained from cpsam on 5 cell lines, training_v2;
+    # F1 0.965 vs cpsam 0.457 on 21 test blocks). Previous: v5 weights
+    # "hemocytometer_retrained_20260825.npy" (HEK293 only), still in the repo.
+    "Hemocytometer Model": "hemocytometer_v6_20261001",
     "General Model": "generalmodel.npy"
 }
 
@@ -48,6 +51,7 @@ MODEL_OPTIONS = {
 # deleted by someone outside the lab. generalmodel.npy here is a byte-identical
 # copy of that one -- it has NOT been retrained.
 MODEL_REPOS = {
+    "hemocytometer_v6_20261001": "LiangLabUMB/cellposecellcounter",
     "hemocytometer_retrained_20260825.npy": "LiangLabUMB/cellposecellcounter",
     "generalmodel.npy": "LiangLabUMB/cellposecellcounter",
 }
@@ -1000,7 +1004,7 @@ def run_segmentation_patched(image_np, model_filename):
     """
     _t_gpu = time.perf_counter()
     h, w = image_np.shape[:2]
-    model_path = hf_hub_download(repo_id=HF_REPO_ID, filename=model_filename)
+    model_path = resolve_model_path(HF_REPO_ID, model_filename)
     if model_filename in loaded_models:
         model = loaded_models[model_filename]
     else: