diff --git a/models/common.py b/models/common.py
index 4f4f331da583..f24ea7885668 100644
--- a/models/common.py
+++ b/models/common.py
@@ -199,7 +199,8 @@ def forward(self, imgs, size=640, augment=False, profile=False):
         shape0, shape1, files = [], [], []  # image and inference shapes, filenames
         for i, im in enumerate(imgs):
             if isinstance(im, str):  # filename or uri
-                im = Image.open(requests.get(im, stream=True).raw if im.startswith('http') else im)  # open
+                im, f = Image.open(requests.get(im, stream=True).raw if im.startswith('http') else im), im  # open
+                im.filename = f  # for uri
             files.append(Path(im.filename).with_suffix('.jpg').name if isinstance(im, Image.Image) else f'image{i}.jpg')
             im = np.array(im)  # to numpy
             if im.shape[0] < 5:  # image in CHW
@@ -253,7 +254,7 @@ def display(self, pprint=False, show=False, save=False, render=False, save_dir='
                     n = (pred[:, -1] == c).sum()  # detections per class
                     str += f"{n} {self.names[int(c)]}{'s' * (n > 1)}, "  # add to string
                 if show or save or render:
-                    img = Image.fromarray(img.astype(np.uint8)) if isinstance(img, np.ndarray) else img  # from np
+                    img = Image.fromarray(img) if isinstance(img, np.ndarray) else img  # from np
                     for *box, conf, cls in pred:  # xyxy, confidence, class
                         # str += '%s %.2f, ' % (names[int(cls)], conf)  # label
                         ImageDraw.Draw(img).rectangle(box, width=4, outline=colors[int(cls) % 10])  # plot