Converted numpy to tensor

app.py

@@ -4,13 +4,15 @@ import math
 import torch
 import numpy as np
 import gradio as gr
+import albumentations
 import matplotlib.pyplot as plt
 from glob import glob
 from PIL import Image
+from pytorch_grad_cam import EigenCAM
 from models.common import DetectMultiBackend
+from albumentations.pytorch import ToTensorV2
 from utils.augmentations import letterbox
 from utils.plots import Annotator, colors
-from pytorch_grad_cam import EigenCAM
 from pytorch_grad_cam.utils.image import show_cam_on_image, scale_cam_image
 from utils.torch_utils import select_device, smart_inference_mode
 from utils.general import check_img_size, Profile, non_max_suppression, scale_boxes
@@ -66,6 +68,13 @@ def inference(input_img, conf_thres, iou_thres, is_false_detection_images=True,
     im0 = input_img.copy()
     im_resized = cv2.resize(im0, (640, 640))
     rgb_img = im_resized.copy()
+    transforms = albumentations.Compose(
+        # Normalize
+        [albumentations.Normalize([0.49139968, 0.48215841, 0.44653091], 
+                                  [0.24703223, 0.24348513, 0.26158784]), 
+        # Convert to tensor                          
+        ToTensorV2()])
+    im_resized = transforms(image = im_resized)['image']
     stride, names, pt = model.stride, model.names, model.pt
     imgsz = check_img_size((640, 640), s=stride)  # check image size