Store hyperparameters as metadata

aris.py

@@ -457,6 +457,9 @@ def create_metadata_table(result, table_headers, info_headers):
             info.append([field_name, str(metadata[field])])
         else:
             info.append([field_name, ""])
+    if 'hyperparameters' in metadata:
+        for param_name in metadata['hyperparameters']:
+            info.append(['**' + param_name + '**', str(metadata['hyperparameters'][param_name])])
     
     return table, info
 

gradio_scripts/result_ui.py

@@ -16,9 +16,9 @@ js_update_tab_labels = """
 
 table_headers = ["TOTAL" , "FRAME_NUM", "DIR", "R", "THETA", "L", "TIME", "DATE", "SPECIES"]
 info_headers = [
-    "TOTAL_TIME", "DATE", "START", "END", "TOTAL_FRAMES", "FRAME_RATE",
-    "TOTAL_FISH", "UPSTREAM_FISH", "DOWNSTREAM_FISH", "NONDIRECTIONAL_FISH",
-    "UPSTREAM_MOTION", "INTENSITY", "THRESHOLD", "WATER_TEMP"
+    "TOTAL_TIME", "DATE", "START", "END", "TOTAL_FRAMES", "FRAME_RATE", "",
+    "TOTAL_FISH", "UPSTREAM_FISH", "DOWNSTREAM_FISH", "NONDIRECTIONAL_FISH", "",
+    "UPSTREAM_MOTION", "INTENSITY", "THRESHOLD", "WATER_TEMP", "",
 ]
 max_tabs = 10
 

main.py

@@ -50,6 +50,13 @@ def predict_task(filepath, weights, conf_thresh, iou_thresh, min_hits, max_age,
     # re-index results if desired - this should be done before writing the file
     results = prep_for_mm(results)
     results = add_metadata_to_result(filepath, results)
+    results['metadata']['hyperparameters'] = {
+        'model': weights,
+        'conf_thresh': conf_thresh,
+        'iou_thresh': iou_thresh,
+        'min_hits': min_hits,
+        'max_age': max_age
+    }
     
     # write output to disk
     json_dump_round_float(results, results_filepath)