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116 lines (88 loc) · 3.94 KB
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!pip install ultralytics
import cv2
cap = cv2.VideoCapture(0)
cap.set(3, 640)
cap.set(4, 480)
while True:
ret, img= cap.read()
cv2.imshow('Webcam', img)
if cv2.waitKey(1) == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
from ultralytics import YOLO
model = YOLO("yolo-Weights/yolov8n.pt")
classNames = ["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat",
"traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat",
"dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella",
"handbag", "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat",
"baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup",
"fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli",
"carrot", "hot dog", "pizza", "donut", "cake", "chair", "sofa", "pottedplant", "bed",
"diningtable", "toilet", "tvmonitor", "laptop", "mouse", "remote", "keyboard", "cell phone",
"microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors",
"teddy bear", "hair drier", "toothbrush"
]
import cv2
cap = cv2.VideoCapture(0)
cap.set(3, 640)
cap.set(4, 480)
while True:
ret, img= cap.read()
results = model(img, stream=True)
cv2.imshow('Webcam', img)
if cv2.waitKey(1) == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
from ultralytics import YOLO
import cv2
import math
# start webcam
cap = cv2.VideoCapture(0) # default cam
cap.set(3, 640)
cap.set(4, 480)
# Yolo model
model = YOLO("yolo-Weights/yolov8n.pt")
# object classes
classNames = ["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck", "boat",
"traffic light", "fire hydrant", "stop sign", "parking meter", "bench", "bird", "cat",
"dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe", "backpack", "umbrella",
"handbag", "tie", "suitcase", "frisbee", "skis", "snowboard", "sports ball", "kite", "baseball bat",
"baseball glove", "skateboard", "surfboard", "tennis racket", "bottle", "wine glass", "cup",
"fork", "knife", "spoon", "bowl", "banana", "apple", "sandwich", "orange", "broccoli",
"carrot", "hot dog", "pizza", "donut", "cake", "chair", "sofa", "pottedplant", "bed",
"diningtable", "toilet", "tvmonitor", "laptop", "mouse", "remote", "keyboard", "cell phone",
"microwave", "oven", "toaster", "sink", "refrigerator", "book", "clock", "vase", "scissors",
"teddy bear", "hair drier", "toothbrush"
]
while True:
success, img = cap.read()
results = model(img, stream=True)
# coordinates
for r in results:
boxes = r.boxes
for box in boxes:
# bounding box
x1, y1, x2, y2 = box.xyxy[0]
x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2) # convert to int values
# put box in cam
cv2.rectangle(img, (x1, y1), (x2, y2), (255, 0, 255), 3)
# confidence
confidence = math.ceil((box.conf[0]*100))/100
print("Confidence is--->",confidence)
# class name
cls = int(box.cls[0])
print("Class name is-->", classNames[cls])
# object details
org = [x1, y1]
font = cv2.FONT_HERSHEY_SIMPLEX
fontScale = 1
color = (255, 0, 0)
thickness = 2
cv2.putText(img, classNames[cls], org, font, fontScale, color, thickness)
cv2.imshow('Webcam', img)
if cv2.waitKey(1) == ord('q'):
break
cap.release()
cv2.destroyAllWindows()