Add File Size (MB) column to benchmarks (ultralytics#8359)

* Add filesize to benchmarks.py

* Add filesize to benchmarks.py

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

utils/benchmarks.py

@@ -41,7 +41,7 @@
 import export
 import val
 from utils import notebook_init
-from utils.general import LOGGER, check_yaml, print_args
+from utils.general import LOGGER, check_yaml, file_size, print_args
 from utils.torch_utils import select_device
 
 
@@ -75,18 +75,19 @@ def run(
             result = val.run(data, w, batch_size, imgsz, plots=False, device=device, task='benchmark', half=half)
             metrics = result[0]  # metrics (mp, mr, map50, map, *losses(box, obj, cls))
             speeds = result[2]  # times (preprocess, inference, postprocess)
-            y.append([name, round(metrics[3], 4), round(speeds[1], 2)])  # mAP, t_inference
+            y.append([name, round(file_size(w), 1), round(metrics[3], 4), round(speeds[1], 2)])  # MB, mAP, t_inference
         except Exception as e:
             LOGGER.warning(f'WARNING: Benchmark failure for {name}: {e}')
-            y.append([name, None, None])  # mAP, t_inference
+            y.append([name, None, None, None])  # mAP, t_inference
         if pt_only and i == 0:
             break  # break after PyTorch
 
     # Print results
     LOGGER.info('\n')
     parse_opt()
     notebook_init()  # print system info
-    py = pd.DataFrame(y, columns=['Format', 'mAP@0.5:0.95', 'Inference time (ms)'] if map else ['Format', 'Export', ''])
+    c = ['Format', 'Size (MB)', 'mAP@0.5:0.95', 'Inference time (ms)'] if map else ['Format', 'Export', '', '']
+    py = pd.DataFrame(y, columns=c)
     LOGGER.info(f'\nBenchmarks complete ({time.time() - t:.2f}s)')
     LOGGER.info(str(py if map else py.iloc[:, :2]))
     return py