Learning Object Detection Detected result showed in discolouration
Breif Description
Recently begin to learning Object Detection, Just starting off with PyTorch, YOLOv5. So I thought why not build a small side project to learn? Using it to train to detect Pikachu.
The Problem
I've successfully trained the model with Pikachu and then uses trained weights with myself written Python script/code to detect the Pikachu using test images, now, here's the problem, Pikachus can successfully detected but all the result showed in blue discolouration, what supposed to be yellow, all turned into blue and blue into yellow.
Fig-1 Result images showed in blue discolouration(few example outputs)
Additional Imformation
I've pushed this project to the GitHub, feel free to download it or pull it to debugging.
GitHub repository where it contains all the files
Any solution/suggestion would be helpful, Thanks.
The Code

&quot;&quot;&quot;Object detection using YOLOv5

Pokemon Pikachu detecting

&quot;&quot;&quot;

# import os, sys to append YOLOv5 folder path
import os, sys

# import object detection needed modules and libraries
# pillow
from PIL import Image, ImageDraw, ImageFont
import numpy as np
import torch # PyTorch


# YOLOv5 folder path and related folder path settings
cwd = os.getcwd()
root_dir = (cwd + &quot;/yolov5_stable&quot;)
sys.path.append(root_dir)


# import methods, functions from YOLOv5
from models.experimental import attempt_load
from utils.datasets import LoadImages
from utils.general import non_max_suppression, scale_coords
from utils.plots import colors



# define a function to show detected pikachu
def show_pikachu(img, det):
    labels = [&quot;pikachu&quot;]
    img = Image.fromarray(img)
    draw = ImageDraw.Draw(img)
    font_size = max(round(max(img.size)/40), 12)
    font = ImageFont.truetype(cwd + &quot;/yolov5_stable/fonts/times.ttf&quot;)

    for info in det:
        color = colors(1)
        target, prob = int(info[5].cpu().numpy()), np.round(info[4].cpu().numpy(), 2)
        x_min, y_min, x_max, y_max = info[0], info[1], info[2], info[3]
        draw.rectangle([x_min, y_min, x_max, y_max], width = 3, outline = color)
        draw.text((x_min, y_min), labels[target] + ':' + str(prob), fill = color, font = font)

    # Bug unresolved, pikachu shown in blue discolouration

    return img


if __name__ == &quot;__main__&quot;:
    device = &quot;cuda:0&quot; if torch.cuda.is_available() else &quot;cpu&quot;
    print(&quot;GPU State: &quot;, device)
    
    data_path = (cwd + &quot;/test_data/&quot;)
    weight_path = (cwd + &quot;/yolov5_stable/weights/best_v1.pt&quot;)
    dataset = LoadImages(data_path)
    model = attempt_load(weight_path, map_location = device)
    model.to(device)
    
    for path, img, im0s, _ in dataset:
        img = torch.from_numpy(img).to(device)
        img = img.float() # uint8 to fp16/32
        img /= 255.0 # 0-255 to 0.0-1.0
        if img.ndimension() == 3:
            img = img.unsqueeze(0)
            
        pred = model(img)[0]
        pred = non_max_suppression(pred, 0.25, 0.45)
        for i, det in enumerate(pred):
            im0 = im0s.copy()
            det[:, :4] = scale_coords(img.shape[2:], det[:, :4], im0.shape).round()
            result = show_pikachu(im0, det)
            result.show()


The problem is that Image.fromarray expects image in RGB and you're providing them in BGR. You just need to change that. There are multiple places you could do that, for instance:
Image.fromarray(img[...,::-1])  # assuming `img` is channel-last

An evidence is that the red parts of the mouse (red is RGB(255, 0, 0)) are being shown in blue (which is RGB(0, 0, 255)). FYI, yellow is RGB(255, 255, 0) and cyan is RGB(0, 255, 255), which you can also see in your case.
