wandb not found

时间: 2023-10-19 13:25:03 浏览: 44
It seems like you're facing an issue with the "wandb" package. "wandb" stands for Weights & Biases, which is a tool for tracking and visualizing machine learning experiments. To resolve this issue, please make sure that you have the package installed on your system. You can install it by running the following command in your terminal or command prompt: ``` pip install wandb ``` If you already have "wandb" installed and you're still encountering the problem, please provide more details about the specific error message or issue you're facing so that I can assist you further.
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ERROR: Could not find a version that satisfies the requirement wandb (from versions: none) ERROR: No matching distribution found for wandb

这个错误提示表明你的系统中没有找到符合要求的wandb软件包版本。可能的原因是你没有正确安装wandb或者你的Python环境不兼容wandb。你可以尝试重新安装wandb或者检查你的Python环境是否满足wandb的要求。另外,你也可以尝试使用其他版本的wandb或者使用其他类似的软件包来替代wandb。

wandb: Currently logged in as: anony-mouse-584351. Use `wandb login --relogin` to force relogin wandb: wandb version 0.15.3 is available! To upgrade, please run: wandb: $ pip install wandb --upgrade wandb: Tracking run with wandb version 0.12.21 wandb: Run data is saved locally in /kaggle/working/yolov7/wandb/run-20230601_125414-1jenk8d0 wandb: Run `wandb offline` to turn off syncing. wandb: Syncing run run12 wandb: ⭐️ View project at https://wandb.ai/anony-mouse-584351/yolov7-tiny?apiKey=323c78e6a061c91ed778f8bd6fc310953f397638 wandb: 🚀 View run at https://wandb.ai/anony-mouse-584351/yolov7-tiny/runs/1jenk8d0?apiKey=323c78e6a061c91ed778f8bd6fc310953f397638 wandb: WARNING Do NOT share these links with anyone. They can be used to claim your runs. /opt/conda/lib/python3.7/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /usr/local/src/pytorch/aten/src/ATen/native/TensorShape.cpp:2227.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] WARNING: Dataset not found, nonexistent paths: ['/kaggle/working/yolov7/noduleyolov1iyolov7pytorch/valid/images'] Traceback (most recent call last): File "yolov7/train.py", line 616, in <module> train(hyp, opt, device, tb_writer) File "yolov7/train.py", line 97, in train check_dataset(data_dict) # check File "/kaggle/working/yolov7/yolov7/utils/general.py", line 173, in check_dataset raise Exception('Dataset not found.') Exception: Dataset not found. wandb: Waiting for W&B process to finish... (failed 1). Press Control-C to abort syncing. wandb: wandb: Synced run12: https://wandb.ai/anony-mouse-584351/yolov7-tiny/runs/1jenk8d0?apiKey=323c78e6a061c91ed778f8bd6fc310953f397638 wandb: Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s) wandb: Find logs at: ./wandb/run-20230601_125414-1jenk8d0/logs

这段信息看起来像是由Wandb库生成的训练日志。首先,它提示你当前登录的帐户是“anony-mouse-584351”,并提供了升级Wandb库的信息。然后它显示了正在追踪的运行信息,包括运行的本地保存路径和Wandb项目和运行的URL链接。它还提供了警告,防止别人使用这些链接来访问或声明您的运行。最后,它显示了一个异常,指出找不到数据集。可能需要检查数据集路径或确保数据集已正确加载。

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there is a file,use c write a System Requirements: A. To make the program as user-friendly as possible, use the following menu to start. 1. Import grades for a course 2. Delete a course 3. Calculate GPA 4. Export file with GPA 5. Quit User will choose the functions using the index number: 1: ask user to import a file from which the grades will be added to students.txt. a) The program should ask the user to input the course name before input the file name. It is assumed that the length of course name is less than 20. b) If the course name inputted by user exists in students.txt, gives user a warning. User can choose to replace the old grades with new or not. If user choose not to replace, go back to main menu. c) If the course name does not exist in students.txt, ask the user to give the file name to import. d) If it is found that a student ID in this imported file cannot be found in the students.txt, do not import and give the warning. Each ID contains 10 digits. It is assumed that each file has been sorted according to ID in ascending order before it is imported. 2: ask user to input the course name to delete. If the course name does not exist in students.txt, gives a warning. 3: the system will calculate GPA for each student in students.txt and put the GPA in the file too. Keep two decimal points in GPA. 4: when user has this choice, the system will display a sub-menu. 1. Sorted in ID (ascending) 2. Sorted in GPA (descending) 3. Back to main menu In this sub-menu, if user chooses 1 or 2, the system will ask user to input a file name to export to. If user chooses 3, system goes back to main menu. 5: Quit the system.

详细解释该代码的思路:import numpy as np import cv2 import random face_cascade = cv2.CascadeClassifier('D:\ANACONDA\pkgs\libopencv-4.7.0-py311h1b74acb_2\Library\etc\haarcascades\haarcascade_frontalface_default.xml') mouth_cascade = cv2.CascadeClassifier('D:\OpenCV_xml\haarcascade_mcs_mouth.xml') bw_threshold = 80 font = cv2.FONT_HERSHEY_SIMPLEX org = (30, 30) weared_mask_font_color = (0, 255, 0) not_weared_mask_font_color = (0, 0, 255) noface = (255, 255, 255) thickness = 2 font_scale = 1 weared_mask = "Thank You for wearing MASK" not_weared_mask = "Please wear MASK to defeat Corona" cap = cv2.VideoCapture(0) while True: ret, img = cap.read() img = cv2.flip(img, 1) gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) (thresh, black_and_white) = cv2.threshold(gray, bw_threshold, 255, cv2.THRESH_BINARY) faces = face_cascade.detectMultiScale(gray, 1.1, 4) faces_bw = face_cascade.detectMultiScale(black_and_white, 1.1, 4) if (len(faces) == 0 and len(faces_bw) == 0): cv2.putText(img, "No face found...", org, font, font_scale, noface, thickness, cv2.LINE_AA) elif (len(faces) == 0 and len(faces_bw) == 1): cv2.putText(img, weared_mask, org, font, font_scale, weared_mask_font_color, thickness, cv2.LINE_AA) else: for (x, y, w, h) in faces: cv2.rectangle(img, (x, y), (x + w, y + h), (255, 255, 255), 2) roi_gray = gray[y:y + h, x:x + w] roi_color = img[y:y + h, x:x + w] mouth_rects = mouth_cascade.detectMultiScale(gray, 1.5, 5) if (len(mouth_rects) == 0): cv2.putText(img, weared_mask, org, font, font_scale, weared_mask_font_color, thickness, cv2.LINE_AA) else: for (mx, my, mw, mh) in mouth_rects: if (y < my < y + h): cv2.putText(img, not_weared_mask, org, font, font_scale, not_weared_mask_font_color, thickness, cv2.LINE_AA) break cv2.imshow('Mask Detection', img) k = cv2.waitKey(30) & 0xff if k == 27: break cap.release() cv2.destroyAllWindows()

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