{"id":710,"date":"2024-02-03T22:09:08","date_gmt":"2024-02-03T14:09:08","guid":{"rendered":"http:\/\/www.tchepai.com\/?p=1"},"modified":"2024-02-03T22:09:08","modified_gmt":"2024-02-03T14:09:08","slug":"hello-world","status":"publish","type":"post","link":"https:\/\/www.kdjingpai.com\/en\/hello-world\/","title":{"rendered":"\u4ee3\u7801\u89e3\u91ca_IT\u4e13\u7528Prompt"},"content":{"rendered":"
\n

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\u6307\u4ee4\u683c\u5f0f<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u4ee3\u7801\u7f16\u8bd1\u5668\uff0c\u89e3\u91ca\u4ee5\u4e0b\u4ee3\u7801\u7247\u6bb5\u7684\u4f5c\u7528\uff0c\u5e76\u8f93\u51fa\u6267\u884c\u7ed3\u679c \u2014\u2014<\/p>\n<\/div>\n

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<font color=”#0000dd”>Python \u4ee3\u7801\u7247\u6bb5<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n

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\u6307\u4ee4\u793a\u4f8b<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u4ee3\u7801\u7f16\u8bd1\u5668\uff0c\u89e3\u91ca\u4ee5\u4e0b\u4ee3\u7801\u7247\u6bb5\u7684\u4f5c\u7528 \u2014\u2014<\/p>\n<\/div>\n

\n

import cv2
\nimport numpy as np
\nimport matplotlib.pyplot as plt
\nimg = cv2.imread(data_path + ‘kxcy.jpg’)
\nplt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
\nplt.show()
\nemboss_kernel = np.array([[-1, 0, 0],
\n[0, 0, 0],
\n[0, 0, 1]])
\nemboss_img = cv2.filter2D(src=img, ddepth=-1, kernel=emboss_kernel)
\nplt.imshow(emboss_img)
\nplt.show()<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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\u4ee3\u7801\u81ea\u52a8\u6ce8\u91ca<\/h1>\n
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\u6307\u4ee4\u683c\u5f0f<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u673a\u5668\u5b66\u4e60\u5de5\u7a0b\u5e08\uff0c\u5bf9\u4e0b\u9762\u7684\u4ee3\u7801\u7247\u6bb5\u52a0\u5165\u4ee3\u7801\u6ce8\u91ca \u2014\u2014<\/p>\n<\/div>\n

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**Python \u4ee3\u7801\u7247\u6bb5<\/p>\n<\/div>\n<\/div>\n<\/div>\n

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\u6307\u4ee4\u793a\u4f8b<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u673a\u5668\u5b66\u4e60\u5de5\u7a0b\u5e08\uff0c\u5bf9\u4e0b\u9762\u7684\u4ee3\u7801\u7247\u6bb5\u52a0\u5165\u4ee3\u7801\u6ce8\u91ca \u2014\u2014<\/p>\n<\/div>\n

\n

import numpy as np
\nimport matplotlib.pyplot as plt
\n%matplotlib inline
\ndef relu(x):
\nreturn np.where(x < 0, 0, x)
\nrelu_inputs = np.arange(-10,10,0.1)
\nrelu_outputs = relu(relu_inputs)
\nplt.plot(relu_inputs,relu_outputs)
\nplt.xlabel(“relu Inputs”)
\nplt.ylabel(“relu Outputs”)
\nplt.show()<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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\u4ee3\u7801\u81ea\u52a8\u6ce8\u91ca<\/h1>\n
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\u6307\u4ee4\u683c\u5f0f<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u8f6f\u4ef6\u5de5\u7a0b\u5e08\uff0c\u4e3a\u4e0b\u9762\u7684\u00a0[\u51fd\u6570\u540d\u79f0]<\/strong>\u00a0\u51fd\u6570\u751f\u6210\u8bf4\u660e\u6587\u6863 \u2014\u2014<\/p>\n<\/div>\n

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\u51fd\u6570\u4ee3\u7801<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n

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\u6307\u4ee4\u793a\u4f8b<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u8f6f\u4ef6\u5de5\u7a0b\u5e08\uff0c\u4e3a\u4e0b\u9762\u7684 [init_network] \u51fd\u6570\u751f\u6210\u8bf4\u660e\u6587\u6863 \u2014\u2014<\/p>\n<\/div>\n

\n

def init_network():
\nnetwork = {}
\nnetwork[‘W1’] = np.array(0.1, 0.3, 0.5], [0.2, 0.4, 0.6)
\nnetwork[‘b1’] = np.array([0.1, 0.2, 0.3])
\nnetwork[‘W2’] = np.array(0.1, 0.4], [0.2, 0.5], [0.3, 0.6)
\nnetwork[‘b2’] = np.array([0.1, 0.2])
\nnetwork[‘W3’] = np.array(0.1, 0.3], [0.2, 0.4)
\nnetwork[‘b3’] = np.array([0.1, 0.2])
\nreturn network<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n

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\u63d0\u9ad8\u4ee3\u7801\u53ef\u8bfb\u6027<\/h1>\n
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\u6307\u4ee4\u683c\u5f0f<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u8f6f\u4ef6\u5de5\u7a0b\u5e08\uff0c\u4f18\u5316\u4e0b\u5217\u4ee3\u7801\u7684\u53ef\u8bfb\u6027 \u2014\u2014 \u2014\u2014<\/p>\n<\/div>\n

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Python \u4ee3\u7801<\/strong><\/p>\n<\/div>\n<\/div>\n<\/div>\n

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\u6307\u4ee4\u793a\u4f8b<\/h3>\n
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\u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u8f6f\u4ef6\u5de5\u7a0b\u5e08\uff0c\u4f18\u5316\u4e0b\u5217\u4ee3\u7801\u7684\u53ef\u8bfb\u6027 \u2014\u2014<\/p>\n<\/div>\n

\n

def list(a,b):
\nrandomCamelCase = a
\nrandon_snake_case = b
\nreturn [randomCanmlCase, random_snake_case]<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

\u6307\u4ee4\u683c\u5f0f \u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u4ee3\u7801\u7f16\u8bd1\u5668\uff0c\u89e3\u91ca\u4ee5\u4e0b\u4ee3\u7801\u7247\u6bb5\u7684\u4f5c\u7528\uff0c\u5e76\u8f93\u51fa\u6267\u884c\u7ed3\u679c \u2014\u2014 <font color=”#0000dd”>Python \u4ee3\u7801\u7247\u6bb5 \u6307\u4ee4\u793a\u4f8b \u8bf7\u4f5c\u4e3a\u4e00\u4e2a\u4ee3\u7801\u7f16\u8bd1\u5668\uff0c\u89e3\u91ca\u4ee5\u4e0b\u4ee3\u7801\u7247\u6bb5\u7684\u4f5c\u7528 \u2014…<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[18],"tags":[23],"class_list":["post-710","post","type-post","status-publish","format-standard","hentry","category-prompts","tag-daima"],"_links":{"self":[{"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/posts\/710","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/comments?post=710"}],"version-history":[{"count":0,"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/posts\/710\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/media?parent=710"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/categories?post=710"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.kdjingpai.com\/en\/wp-json\/wp\/v2\/tags?post=710"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}