Update app.py

app.py

@@ -1,11 +1,15 @@
-# RUN BELOW FIRST THEN RUN BELOW
 
-# First run the code to get the validation metrics of best.pt
+
+
 
 from ultralytics import YOLO
 
-model_path = "best.pt"  # your trained model
-data_yaml_path = "/content/bccd_rbc_wbc_platelets-1/data.yaml"  # dataset configuration file
+# RUN BELOW FIRST THEN RUN BELOW
+
+# First run the code to get the validation metrics of best.pt
+
+#model_path = "best.pt"  # your trained model and use exact file location
+#data_yaml_path = "data.yaml"  # dataset configuration file and use exact data.yaml file location
 
 #model = YOLO(model_path)
 #metrics = model.val(data=data_yaml_path)  # ensure data.yaml points to the correct valid set
@@ -35,13 +39,12 @@ data_yaml_path = "/content/bccd_rbc_wbc_platelets-1/data.yaml"  # dataset config
 #    print(f"{cname}: Precision={p}, Recall={r}, mAP50={ap50}, mAP50-95={ap}")
 
 
+## End of Validation
 
 ############ Take the values from abover and put them below manually
 
-
 ############## Use below for production with manual metrics input
 
-
 import os
 import torch
 import cv2