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ter(valid_pct=0.2,seed=42),get_y=parent_label,item_tfms=Resize(128))objects=objects.new(item_tfms=Crop(Resized224,min_scale=0.5),batch_tfms=aug_transforms())dls=objects.dataloaders(path)learner=cnn_learner(dls,resnet18,metrics=error_rate)learner.fine_tune(3)epochtrain_lossvalid_losserror_ratetime0501.6635559011epochtrain_lossvalid_losserror_ratetime00.4582120.2268660.09174301:3210.3583640.1452860.03669701:3120.2815170.1464770.03669701:32濡傛灉浣犳敞鎰忓埌error_rate鍦ㄥ悗闈㈢殑epoch鏈変笂鍗囩殑璇濓紝鍙互闄嶄綆fine_tune鐨勫弬鏁颁互杈惧埌鏈€濂界殑Effect.Becauseiftherearetoomanytrainingrounds,themodelwilloverfitthetrainingset,andtheerrorratewillbecomehigherwhenencounteringnewdata.浠庝笂闈㈢殑杈撳嚭鍙互鐪嬪嚭锛屽噯纭巼宸茬粡鎻愰珮鍒?6%浠ヤ笂銆傝揪鍒版弧鎰忕殑鍑嗙‘鐜囧悗锛屽嵆鍙皢妯″瀷瀵煎嚭骞跺湪绾夸娇鐢ㄣ€備互涓嬩唬鐮佽浼氬皢妯″瀷淇濆瓨鍒癳xport.pkl銆俵earner.export()鍚庣API鍚庣API鏄繖涓」鐩腑鏈€绠€鍗曠殑閮ㄥ垎锛屽彧鏈変竴涓鐐广€傚姞杞戒箣鍓嶅鍑虹殑妯″瀷锛屽苟鍦ㄦ敹鍒版柊鍥剧墖鏃朵娇鐢ㄨ妯″瀷棰勬祴鍒嗙被銆倀rump=load_learner('model.pkl')@app.route('/api/1.0/classify-image',methods=['POST'])defclassify():image=request.files['image']res=trump.predict(image.read())response=jsonify({'result':res[0]})response.status_code=200returnresponse瀹屾暣浠ｇ爜鍦℅itHub涓娿€傛寜鐓ф枃妗ｉ儴缃插埌LeanCloud浜戝紩鎿庛€傚墠绔綉绔欏墠绔篃姣旇緝绠€鍗曘€傚畠鍙渶瑕佷竴涓〉闈緵鐢ㄦ埛涓婁紶鐓х墖锛屽湪娴忚鍣ㄤ腑缂╁皬鐓х墖骞跺彂閫佸埌鍚庣API銆傚畬鏁寸殑React椤圭洰鍦℅itHub涓婏紝涓昏浠ｇ爜鍦ˋpp.js涓€傞檺浜庣瘒骞咃紝鎴戝氨涓嶇粏璇翠簡锛屽彧闄勪笂杩愯鎴浘锛氬ぇ瀹跺彲鑳藉凡缁忔敞鎰忓埌锛屼笂闈㈢殑鍚庣API鏈嶅姟鏄棤鐘舵€佺殑锛屼笉瀛樺偍浠讳綍鏁版嵁锛屾墍浠ュ叾瀹炶瘑鍒繃绋嬪彲浠ュ湪鍓嶇Finish瀹屾垚銆傛湁鍏磋叮鐨勫彲浠ョ爺绌朵竴涓嬪浣曞皢PyTorch妯″瀷杞崲涓篔avaScript鍙敤鐨勬ā鍨嬶紝骞跺皾璇曠洿鎺ュ湪娴忚鍣ㄤ腑璇嗗埆鐓х墖銆傚湪瀹為檯搴旂敤涓紝杩欑鏂规硶涓嶉渶瑕佸悜鏈嶅姟鍣ㄤ紶杈撲换浣曟暟鎹紝鍙互寰堝ソ鍦颁繚鎶ょ敤鎴烽殣绉併€傝繖涔熸槸Apple姝ｅ湪鎺ㄥ姩鐨刼n-devicemachinelearning鐨勬柟鍚戙€傚浘鍍忚瘑鍒槸鏈哄櫒瀛︿範鍙互瑙ｅ喅鐨勬渶绠€鍗曠殑涓€绫婚棶棰橈紝鍥犱负鏈夊緢澶氱幇鎴愮殑缁撴灉鍙互閲嶅浣跨敤锛屾柊鐨勫簲鐢ㄥ嵆浣垮彧闇€瑕佸皯閲忕殑璁粌鏁版嵁涔熻兘鍙栧緱鏇村ソ鐨勬晥鏋溿€傝繕鏈夎澶氬叾浠栫被鍨嬬殑闂涓嶅鏄撳緱鍒颁护浜烘弧鎰忕殑缁撴灉銆侺eanCloud鐩墠姝ｅ湪寮€鍙戞満鍣ㄥ涔犳柟闈㈢殑鏂颁骇鍝侊紝甯姪寮€鍙戣€呮洿瀹规槗鍦板彂鐜版暟鎹殑浠峰€笺€傚鏋滀綘瀵规鎰熷叴瓒ｏ紝鍙互鍏虫敞鎴戜滑鐨勫井鍗氥€佸井淇″叕浼楀彿銆佹帹鐗癸紝鎴栬€呮敞鍐屾垚涓篖eanCloud鐢ㄦ埛銆傛垜浠皢鍦ㄨ繎鏈熷叕甯冩洿澶氫俊鎭紝骞堕個璇烽儴鍒嗙敤鎴疯瘯鐢ㄦ柊浜у搧銆傛爣棰樺浘CharlesDeluvio
