diff --git a/utils/plots.py b/utils/plots.py
index 7af3dc5..a9b5870 100644
--- a/utils/plots.py
+++ b/utils/plots.py
@@ -1,13 +1,13 @@
 # Plotting utils
 
 import glob
-import math
 import os
 import random
 from copy import copy
 from pathlib import Path
 
 import cv2
+import math
 import matplotlib
 import matplotlib.pyplot as plt
 import numpy as np
@@ -218,13 +218,13 @@ def plot_targets_txt():  # from utils.plots import *; plot_targets_txt()
     plt.savefig('targets.jpg', dpi=200)
 
 
-def plot_study_txt(f='study.txt', x=None):  # from utils.plots import *; plot_study_txt()
+def plot_study_txt(path='', x=None):  # from utils.plots import *; plot_study_txt()
     # Plot study.txt generated by test.py
     fig, ax = plt.subplots(2, 4, figsize=(10, 6), tight_layout=True)
     ax = ax.ravel()
 
     fig2, ax2 = plt.subplots(1, 1, figsize=(8, 4), tight_layout=True)
-    for f in ['study/study_coco_%s.txt' % x for x in ['yolov5s', 'yolov5m', 'yolov5l', 'yolov5x']]:
+    for f in [Path(path) / f'study_coco_{x}.txt' for x in ['yolov5s', 'yolov5m', 'yolov5l', 'yolov5x']]:
         y = np.loadtxt(f, dtype=np.float32, usecols=[0, 1, 2, 3, 7, 8, 9], ndmin=2).T
         x = np.arange(y.shape[1]) if x is None else np.array(x)
         s = ['P', 'R', 'mAP@.5', 'mAP@.5:.95', 't_inference (ms/img)', 't_NMS (ms/img)', 't_total (ms/img)']
@@ -234,7 +234,7 @@ def plot_study_txt(f='study.txt', x=None):  # from utils.plots import *; plot_st
 
         j = y[3].argmax() + 1
         ax2.plot(y[6, :j], y[3, :j] * 1E2, '.-', linewidth=2, markersize=8,
-                 label=Path(f).stem.replace('study_coco_', '').replace('yolo', 'YOLO'))
+                 label=f.stem.replace('study_coco_', '').replace('yolo', 'YOLO'))
 
     ax2.plot(1E3 / np.array([209, 140, 97, 58, 35, 18]), [34.6, 40.5, 43.0, 47.5, 49.7, 51.5],
              'k.-', linewidth=2, markersize=8, alpha=.25, label='EfficientDet')
@@ -246,8 +246,7 @@ def plot_study_txt(f='study.txt', x=None):  # from utils.plots import *; plot_st
     ax2.set_xlabel('GPU Speed (ms/img)')
     ax2.set_ylabel('COCO AP val')
     ax2.legend(loc='lower right')
-    plt.savefig('study_mAP_latency.png', dpi=300)
-    plt.savefig(f.replace('.txt', '.png'), dpi=300)
+    plt.savefig('test_study.png', dpi=300)
 
 
 def plot_labels(labels, save_dir=''):