پردازش تصویر با استفاده از روش simsiam
سه سال پیش منتشر شده
تعداد بازدید: 259
کد پروژه: 408407
شرح پروژه
سلام دوستان.
من یک پروژه ی پردازش تصویر دارم که حجم کل تصاویری که دارم حدودا 100 گیگ هستش و باید مدل simsiam رو روی این داده ها اجرا کنم. مشکل من این هست که چون داده هام زیاد هستن میخواستم مدل simsiam رو با استفاده از spark اجرا کنم ولی مدام ارور زیر رو میگیرم. کدهارو نوشتم ولی هرراهی که امتحان میکنم این مشکل حل نمیشه. نمیدونم ایراد دقیقا از چی هست.
پ.ن : 1. لینک زیر مربوط به الگوریتم simsiam در keras هستش، که میخوام این الگوریتم رو با spark اجرا کنم.
https://keras.io/examples/vision/simsiam/
2.در فایلی که پیوست شده وقتی با دستور show میخوایم دیتافریم رو نمایش بدیم و یا با دستور select و print میخوایم یک ستون از دیتافریم رو پرینت کنیم ارور میده.
3. اگر توضیحی در مورد کدها نیاز هست در خدمتتون هستم.
ممنون میشم اگه کسی بتونه بهم کمک کنه. البته هیچ اجباری وجودنداره که حتما با استفاده از spark کار انجام بشه. اگه بشه این حجم از داده رو با مدل simsiam بدون spark هم اجرا کنم هیچ مشکلی نداره.
با تشکر فراوان
Py4JJavaError: An error occurred while calling o84.showString. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0) (67afa9b66146 executor driver): java.io.FileNotFoundException: File file:/content/gdrive/My%20Drive/ALLimges/Patient%201/CT/IMG-0001-00001.jpg does not exist It is possible the underlying files have been updated. You can explicitly invalidate the cache in Spark by running 'REFRESH TABLE tableName' command in SQL or by recreating the Dataset/DataFrame involved. at org.apache.spark.sql.errors.QueryExecutionErrors$.readCurrentFileNotFoundError(QueryExecutionErrors.scala:661) at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:212) at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:270) at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:116) at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:364) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:890) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:890) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365) at org.apache.spark.rdd.RDD.iterator(RDD.scala:329) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:136) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1504) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551) at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128) at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628) at java.base/java.lang.Thread.run(Thread.java:829) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2672) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2608) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2607) at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2607) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1182) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1182) at scala.Option.foreach(Option.scala:407) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1182) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2860) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2802) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2791) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:952) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2238) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2259) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2278) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:506) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:459) at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48) at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3868) at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2863) at org.apache.spark.sql.Dataset.$anonfun$withAction$2(Dataset.scala:3858) at org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:510) at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3856) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:109) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:169) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:95) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:779) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3856) at org.apache.spark.sql.Dataset.head(Dataset.scala:2863) at org.apache.spark.sql.Dataset.take(Dataset.scala:3084) at org.apache.spark.sql.Dataset.getRows(Dataset.scala:288) at org.apache.spark.sql.Dataset.showString(Dataset.scala:327) at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.base/java.lang.reflect.Method.invoke(Method.java:566) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at py4j.Gateway.invoke(Gateway.java:282) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182) at py4j.ClientServerConnection.run(ClientServerConnection.java:106) at java.base/java.lang.Thread.run(Thread.java:829) Caused by: java.io.FileNotFoundException: File file:/content/gdrive/My%20Drive/ALLimges/Patient%201/CT/IMG-0001-00001.jpg does not exist It is possible the underlying files have been updated. You can explicitly invalidate the cache in Spark by running 'REFRESH TABLE tableName' command in SQL or by recreating the Dataset/DataFrame involved. at org.apache.spark.sql.errors.QueryExecutionErrors$.readCurrentFileNotFoundError(QueryExecutionErrors.scala:661) at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:212) at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:270) at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:116) at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:364) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:890) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:890) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:365) at org.apache.spark.rdd.RDD.iterator(RDD.scala:329) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:136) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1504) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551) at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128) at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628) ... 1 more
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