Remove multiprocessing as it seems to be breaking

python_utils/running_model.py

@@ -110,6 +110,7 @@ def process_file(file, predictor_=None):
     else:
         # otherwise use the passed predictor
         prediction = predictor_(im)
+    print(prediction)
     return {
         "filename": file["name"],
         "image": img_base64,
@@ -122,10 +123,13 @@ def run_predictions(files):
 
     ## When using GPU, run single instance
     ## Or if not checking many files, as loading multiple models isn't worthwhile
-    if torch.cuda.is_available() or len(files) < 4:
+    if True:#torch.cuda.is_available() or len(files) < 4:
+        print(f'Using 1 process')
+
+        predictor_ = load_model()
+
         for file in files:
             # Run prediction with original BGR image
-            predictor_ = load_model()
             prediction_output = process_file(file, predictor_=predictor_)
 
             results.append(prediction_output)