How to use trained yolov7 best.pt file as "vehicle plate detection" application in python? - yolo

Question

I have trained a model using yolov7 https://colab.research.google.com/drive/1X9A8odmK4k6l26NDviiT6dd6TgR-piOa#scrollTo=nD-uPyQ_2jiN colab file. After training I got a file named best.pt and I want to use it as a service/application in python. There is a yolov3 example which I created. This one was using .weights so how can I use .pt?
import cv2
import numpy as np
import time
import os
def getPhoto():
ROOT_DIR = os.path.dirname(__file__)
URL = "http://192.168.1.3:4747/video"
PC_CAM = 0
net = cv2.dnn.readNet(
f"{ROOT_DIR}\\yolov3_custom_final.weights",
f"{ROOT_DIR}\\yolov3_custom.cfg",
)
classes = []
with open(f"{ROOT_DIR}\\classes.txt", "r") as f:
classes = f.read().splitlines()
timeElapsed = 0
wCam, hCam = 640, 360
font = cv2.FONT_HERSHEY_PLAIN
colors = np.random.uniform(0, 255, size=(2, 3))
cap = cv2.VideoCapture(URL)
cap.set(3, wCam)
cap.set(4, hCam)
while True:
_, img = cap.read()
cv2.imshow("Detection Screen", img)
if cv2.waitKey(1) == ord("c"):
break
height, width, _ = img.shape
blob = cv2.dnn.blobFromImage(
img, 1 / 255, (416, 416), (0, 0, 0), swapRB=True, crop=False
)
net.setInput(blob)
output_layers_names = net.getUnconnectedOutLayersNames()
layerOutputs = net.forward(output_layers_names)
boxes = []
confidences = []
class_ids = []
for output in layerOutputs:
for detection in output:
scores = detection[5:]
class_id = np.argmax(scores)
confidence = scores[class_id]
if confidence > 0.6:
center_x = int(detection[0] * width)
center_y = int(detection[1] * height)
w = int(detection[2] * width)
h = int(detection[3] * height)
x = int(center_x - w / 2)
y = int(center_y - h / 2)
boxes.append([x, y, w, h])
confidences.append((float(confidence)))
class_ids.append(class_id)
indexes = cv2.dnn.NMSBoxes(boxes, confidences, 0.2, 0.4)
if len(indexes) > 0:
for i in indexes.flatten():
x, y, w, h = boxes[i]
label = str(classes[class_ids[i]])
confidence = str(round(confidences[i], 2))
color = colors[i]
cv2.rectangle(img, (x, y), (x + w, y + h), color, 2)
cv2.putText(
img,
label + " " + confidence,
(x, y + 20),
font,
2,
(255, 255, 0),
2,
)
cv2.imwrite(f"{ROOT_DIR}\\DetectedPhoto.jpg", img)
print("Image Saved")
getPhoto()
I want to detect vehicle plates using .pt file and cut vehicle plates and save them as .jpeg.

Answer 1

you can do this with detect.py insided yolov7 folder. Run this:
python detect.py --weights best.pt --source image.jpg
you can download yolov7 with this method:
git clone https://github.com/WongKinYiu/yolov7.git
in yolov7 you can see detect.py