From 9396b65297a83b7ae8a77cd8869d393536f39e28 Mon Sep 17 00:00:00 2001 From: Ryan Date: Mon, 26 Jun 2023 17:12:51 +0800 Subject: [PATCH] Mon Jun 26 05:12:51 PM CST 2023 --- demo.py | 53 --------------------------- detect_image.py | 0 detect_video.py | 0 image/182786930_7ea28fa4e5_b.jpg | Bin 0 -> 160500 bytes image/19749927709_0fc8e147f4_c.jpg | Bin 0 -> 95696 bytes image/1_3B491ZMKZXn_8wNZzzmLjw.png | Bin 0 -> 260645 bytes image/2216426419_5ecce6a9b7_b.jpg | Bin 0 -> 88149 bytes image/2216427485_4ab4a0ab15_b.jpg | Bin 0 -> 88261 bytes image/26042575973_bec0ee4ed3_c.jpg | Bin 0 -> 68679 bytes image/262351090_cce46a3aaf_b.jpg | Bin 0 -> 170685 bytes image/262351090_cce46a3aaf_c.jpg | Bin 0 -> 125433 bytes image/2637982077_a3eae26779.jpg | Bin 0 -> 118766 bytes image/26580716151_231617fa62_c.jpg | Bin 0 -> 62654 bytes image/3141147409_a21cf55a3f_b.jpg | Bin 0 -> 82569 bytes image/3141148575_fa707caa51_b.jpg | Bin 0 -> 69019 bytes image/3192850778_a357a8c4eb_b.jpg | Bin 0 -> 40889 bytes 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image/4590208246_9fe6b3ba4e_b.jpg create mode 100644 image/5080604905_a3fa44daa2_c.jpg create mode 100644 image/517635286_226efba7b5_z.jpg create mode 100644 image/52919232835_7efa5ba569_c.jpg create mode 100644 image/5345628611_c298fc968b_c.jpg create mode 100644 image/5348993466_40cde6a06d_c.jpg create mode 100644 image/5751900082_3b019aa0f3_c.jpg create mode 100644 image/6324133464_9605f83c27_c.jpg create mode 100644 image/6364195427_0dca317ef3_c.jpg create mode 100644 image/7454489180_bf2aeb87de_c.jpg create mode 100644 image/FIKXSKACURH2DK7M6K6QTPZN5U.jpg create mode 100644 image/maxresdefault.jpg create mode 100644 image/rubikscube-2048px-08408.jpg create mode 100644 train.py create mode 100644 yolov8n.pt diff --git a/demo.py b/demo.py deleted file mode 100644 index f01c4f1..0000000 --- a/demo.py +++ /dev/null @@ -1,53 +0,0 @@ -from ultralytics import YOLO -# from ultralytics.yolo.utils.benchmarks import benchmark 。 -import cv2 - -# Load a model -# model = YOLO("yolov8n.yaml") # build a new model from scratch -model = YOLO("yolov8n.pt") # load a pretrained model (recommended for training) - -# Use the model -# model.train(data="coco128.yaml", epochs=3,workers=0) # train the model,workers=0 if windows -# metrics = model.val() # evaluate model performance on the validation set -''' -results = model("bus.jpg") # predict on an image -print(results) -# ''' -img_path = "./image/" -# results = model.predict(img_path, save=True,conf=0.5) # device=0 by default, conf:置信度阈值 -# results = model.predict(img_path,save=True,classes=[0,2],conf=0.5) # i.e. classes=0,classes=[0,3,4] - -# save detection results * -# results = model.predict(img_path,save=True,save_txt=True,classes=0,conf=0.4) - - - -# predict video -video_path = "./video/1.mp4" -cap = cv2.VideoCapture(0) - -# Loop through the video frames -while cap.isOpened(): - # Read a frame from the video - success, frame = cap.read() - - if success: - # Run YOLOv8 inference on the frame - results = model(frame) - - # 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