Frame adjustment

client/dive-common/apispec.ts

@@ -168,7 +168,7 @@ interface Api {
   getTileURL?(itemId: string, x: number, y: number, level: number, query: Record<string, any>):
    string;
   importAnnotationFile(id: string, path: string, file?: File,
-    additive?: boolean, additivePrepend?: string, set?: string): Promise<boolean>;
+    additive?: boolean, additivePrepend?: string, set?: string): Promise<boolean | string[]>;
 }
 const ApiSymbol = Symbol('api');
 

client/dive-common/components/ImportAnnotations.vue

@@ -52,7 +52,7 @@
         if (!ret.canceled) {
           menuOpen.value = false;
           const path = ret.filePaths[0];
-          let importFile = false;
+          let importFile: boolean | string[] = false;
           processing.value = true;
           const set = currentSet.value === 'default' ? undefined : currentSet.value;
           if (ret.fileList?.length) {
@@ -74,6 +74,17 @@
               set,
             );
           }
+          console.log(importFile);
+          if (Array.isArray(importFile) && importFile.length) {
+            const text = ['There were warnings when importing. While the data imported properly please double check your annotations',
+              'Below is a list of information that can help with debugging',
+            ].concat(importFile as string[]);
+            await prompt({
+              title: 'Import Warnings',
+              text,
+              positiveButton: 'OK',
+            });
+          }
 
           if (importFile) {
             processing.value = false;
@@ -188,7 +199,7 @@
                 outlined
                 small
               >
-                <template v-slot:selection="{ attrs, item, selected }">
+                <template #selection="{ attrs, item, selected }">
                   <v-chip
                     v-bind="attrs"
                     small

client/platform/desktop/backend/cli.ts

@@ -52,7 +52,7 @@ function updater(update: DesktopJobUpdate) {
 
 async function parseViameFile(file: string) {
   const data = await parseFile(file);
-  stdout.write(JSON.stringify(data));
+  stdout.write(JSON.stringify(data[0]));
 }
 
 async function parseJsonFile(filepath: string, metapath: string) {

client/platform/desktop/backend/ipcService.ts

@@ -99,6 +99,9 @@ export default function register() {
     id, path, additive, additivePrepend,
   }: { id: string; path: string; additive: boolean; additivePrepend: string }) => {
     const ret = await common.dataFileImport(settings.get(), id, path, additive, additivePrepend);
+    console.log(ret.warnings);
+    if (ret.warnings.length)
+      return ret.warnings;
     return ret;
   });
 

client/platform/desktop/backend/native/common.ts

@@ -578,13 +578,14 @@ async function _ingestFilePath(
   imageMap?: Map<string, number>,
   additive = false,
   additivePrepend = '',
-): Promise<(DatasetMetaMutable & { fps?: number }) | null> {
+): Promise<[(DatasetMetaMutable & { fps?: number }), string[]] | null> {
   if (!fs.existsSync(path)) {
     return null;
   }
   if (fs.statSync(path).size === 0) {
     return null;
   }
+  let warnings: string[] = [];
   // Make a copy of the file in aux
   const projectInfo = getProjectDir(settings, datasetId);
   const newPath = npath.join(projectInfo.auxDirAbsPath, `imported_${npath.basename(path)}`);
@@ -612,9 +613,10 @@ async function _ingestFilePath(
   } else if (CsvFileName.test(path)) {
     // VIAME CSV File
     const data = await viameSerializers.parseFile(path, imageMap);
-    annotations.tracks = data.tracks;
-    annotations.groups = data.groups;
-    meta.fps = data.fps;
+    annotations.tracks = data[0].tracks;
+    annotations.groups = data[0].groups;
+    meta.fps = data[0].fps;
+    [, warnings] = data;
   } else if (YAMLFileName.test(path)) {
     annotations = await kpf.parse([path]);
   }
@@ -652,7 +654,7 @@ async function _ingestFilePath(
     await _saveSerialized(settings, datasetId, annotations, true);
   }
 
-  return meta;
+  return [meta, warnings];
 }
 
 /**
@@ -679,17 +681,20 @@ async function ingestDataFiles(
 ): Promise<{
   processedFiles: string[];
   meta: DatasetMetaMutable & { fps?: number };
+  warnings: string[];
 }> {
   const processedFiles = []; // which files were processed to generate the detections
   const meta = {};
-
+  let outwarnings: string[] = [];
   for (let i = 0; i < absPaths.length; i += 1) {
     const path = absPaths[i];
     // eslint-disable-next-line no-await-in-loop
-    const newMeta = await _ingestFilePath(
+    const results = await _ingestFilePath(
       settings, datasetId, path, imageMap, additive, additivePrepend,
     );
-    if (newMeta !== null) {
+    if (results !== null) {
+      const [newMeta, warnings] = results;
+      outwarnings = warnings;
       merge(meta, newMeta);
       processedFiles.push(path);
     }
@@ -702,15 +707,17 @@ async function ingestDataFiles(
       const path = cameraAndPath[i][1];
       const cameraDatasetId = `${datasetId}/${cameraName}`;
       // eslint-disable-next-line no-await-in-loop
-      const newMeta = await _ingestFilePath(settings, cameraDatasetId, path, imageMap);
-      if (newMeta !== null) {
+      const results = await _ingestFilePath(settings, cameraDatasetId, path, imageMap);
+      if (results !== null) {
+        const [newMeta, warnings] = results;
+        outwarnings = outwarnings.concat(warnings);
         merge(meta, newMeta);
         processedFiles.push(path);
       }
     }
   }
 
-  return { processedFiles, meta };
+  return { processedFiles, meta, warnings: outwarnings };
 }
 /**
  * Need to take the trained pipeline if it exists and place it in the DIVE_Pipelines folder

client/platform/desktop/backend/serializers/viame.spec.ts

@@ -239,9 +239,9 @@ describe('VIAME Python Compatibility Check', () => {
       const trackArray = Object.values(trackData);
       // eslint-disable-next-line no-await-in-loop
       const results = await parse(csvStream);
-      expect(Object.values(results.tracks)).toEqual(trackArray);
+      expect(Object.values(results[0].tracks)).toEqual(trackArray);
       // eslint-disable-next-line no-await-in-loop
-      const attData = processTrackAttributes(Object.values(results.tracks));
+      const attData = processTrackAttributes(Object.values(results[0].tracks));
       expect(testAttributes).toEqual(attData.attributes);
     }
   });
@@ -314,7 +314,7 @@ describe('Test Image Filenames', () => {
       } else {
         // eslint-disable-next-line no-await-in-loop
         const result = await parseFile(testPath, imageMap);
-        expect(Object.values(result.tracks).length).toBeGreaterThan(0);
+        expect(Object.values(result[0].tracks).length).toBeGreaterThan(0);
       }
     }
   });

client/platform/desktop/backend/serializers/viame.ts

@@ -241,7 +241,7 @@ function _parseFeature(row: string[]) {
   };
 }
 
-async function parse(input: Readable, imageMap?: Map<string, number>): Promise<AnnotationFileData> {
+async function parse(input: Readable, imageMap?: Map<string, number>): Promise<[AnnotationFileData, string[]]> {
   const parser = csvparser({
     delimiter: ',',
     // comment lines may not have the correct number of columns
@@ -253,8 +253,9 @@ async function parse(input: Readable, imageMap?: Map<string, number>): Promise<A
   const foundImages: {image: string; frame: number; csvFrame: number}[] = [];
   let error: Error | undefined;
   let multiFrameTracks = false;
+  const warnings: string[] = [];
 
-  return new Promise<AnnotationFileData>((resolve, reject) => {
+  return new Promise<[AnnotationFileData, string[]]>((resolve, reject) => {
     pipeline([input, parser], (err) => {
       // undefined err indicates successful exit
       if (err !== undefined) {
@@ -280,15 +281,17 @@ async function parse(input: Readable, imageMap?: Map<string, number>): Promise<A
           }
           const k = i + 1;
           if (k < filteredImages.length) {
-            if (filteredImages[i].csvFrame + 1 !== filteredImages[k].csvFrame || filteredImages[i].frame + 1 !== filteredImages[k].frame) {
+            const itemDifference = foundImages[k].csvFrame - filteredImages[i].csvFrame;
+            if (
+              foundImages[i].csvFrame + itemDifference !== filteredImages[k].csvFrame || filteredImages[i].frame + itemDifference !== filteredImages[k].frame) {
             // We have misaligned image sequences so we error out
-              error = new Error(`A subsampling of images were used with the CSV but they were not sequential\n 
+              warnings.push(`A subsampling of images were used with the CSV but they were not sequential\n 
                 ${filteredImages[i].csvFrame + 1} !== ${filteredImages[k].csvFrame} || ${filteredImages[i].frame + 1} !== ${filteredImages[k].frame}\n
                 image1: ${filteredImages[i].image} image2: ${filteredImages[k].image} - these should be sequential in the CSV
               \n`);
             }
           }
-          frameMapper[filteredImages[i].csvFrame] = i;
+          frameMapper[filteredImages[i].csvFrame] = filteredImages[i].frame;
           minFrame = Math.min(minFrame, filteredImages[i].csvFrame);
           maxFrame = Math.max(maxFrame, filteredImages[i].csvFrame);
         }
@@ -347,7 +350,9 @@ async function parse(input: Readable, imageMap?: Map<string, number>): Promise<A
           if (k < foundImages.length) {
             if (foundImages[i].csvFrame > foundImages[k].csvFrame || foundImages[i].frame > foundImages[k].frame) {
             // We have misaligned video sequences so we error out
-              error = new Error('Images were provided in an unexpected order and dataset contains multi-frame tracks.');
+              warnings.push(`Images were provided in an unexpected order and dataset contains multi-frame tracks.\n
+              image${i}: frame: ${foundImages[i].frame} csvFrame: ${foundImages[i].csvFrame}
+              image${k}: frame: ${foundImages[k].frame} csvFrame: ${foundImages[k].csvFrame}`);
             }
           }
         }
@@ -357,7 +362,7 @@ async function parse(input: Readable, imageMap?: Map<string, number>): Promise<A
       if (error !== undefined) {
         reject(error);
       }
-      resolve({ tracks, groups: {}, fps });
+      resolve([{ tracks, groups: {}, fps }, warnings]);
     });
     parser.on('readable', () => {
       let record: string[];
@@ -407,8 +412,10 @@ async function parse(input: Readable, imageMap?: Map<string, number>): Promise<A
             });
             if (rowInfo.frame < maxFeatureFrame) {
             // trackId was already in dataMap, and frame is out of order
-              error = new Error(
-                'annotations were provided in an unexpected order and dataset contains multi-frame tracks',
+              warnings.push(
+                `annotations were provided in an unexpected order and dataset contains multi-frame tracks:
+                id: ${rowInfo.id}  filename: ${rowInfo.filename}  frame: ${rowInfo.frame}
+                maxFeatureFrame: ${maxFeatureFrame}`,
               );
               // eslint-disable-next-line no-continue
               continue;
@@ -446,7 +453,7 @@ async function parse(input: Readable, imageMap?: Map<string, number>): Promise<A
 }
 
 async function parseFile(path: string, imageMap?: Map<string, number>):
-  Promise<AnnotationFileData> {
+  Promise<[AnnotationFileData, string[]]> {
   const stream = fs.createReadStream(path);
   return parse(stream, imageMap);
 }

client/platform/desktop/frontend/api.ts

@@ -133,7 +133,7 @@ function importMultiCam(args: MultiCamImportArgs):
 }
 
 // eslint-disable-next-line @typescript-eslint/no-unused-vars
-function importAnnotationFile(id: string, path: string, _htmlFile = undefined, additive = false, additivePrepend = ''): Promise<boolean> {
+function importAnnotationFile(id: string, path: string, _htmlFile = undefined, additive = false, additivePrepend = ''): Promise<boolean | string[]> {
   return ipcRenderer.invoke('import-annotation', {
     id, path, additive, additivePrepend,
   });

client/platform/web-girder/api/dataset.service.ts

@@ -88,7 +88,7 @@ function makeViameFolder({
   );
 }
 
-async function importAnnotationFile(parentId: string, path: string, file?: HTMLFile, additive = false, additivePrepend = '', set: string | undefined = undefined) {
+async function importAnnotationFile(parentId: string, path: string, file?: HTMLFile, additive = false, additivePrepend = '', set: string | undefined = undefined): Promise<boolean | string[]> {
   if (file === undefined) {
     return false;
   }
@@ -111,6 +111,11 @@ async function importAnnotationFile(parentId: string, path: string, file?: HTMLF
     });
     if (uploadResponse.status === 200) {
       const final = await postProcess(parentId, true, false, additive, additivePrepend, set);
+      if (final.data.length > 1) {
+        const warnings = final.data[1];
+        return warnings;
+      }
+
       return final.status === 200;
     }
   }

client/platform/web-girder/api/rpc.service.ts

@@ -1,8 +1,9 @@
 import girderRest from 'platform/web-girder/plugins/girder';
+import type { GirderModel } from '@girder/components/src';
 import { Pipe } from 'dive-common/apispec';
 
 function postProcess(folderId: string, skipJobs = false, skipTranscoding = false, additive = false, additivePrepend = '', set: string | undefined = undefined) {
-  return girderRest.post(`dive_rpc/postprocess/${folderId}`, null, {
+  return girderRest.post<[GirderModel, string[]]>(`dive_rpc/postprocess/${folderId}`, null, {
     params: {
       skipJobs, skipTranscoding, additive, additivePrepend, set,
     },

client/platform/web-girder/views/Export.vue

@@ -319,15 +319,16 @@ export default defineComponent({
                   class="mt-2"
                   :disabled="!exportUrls.exportDetectionsUrl"
                   @click="doExport({ url: exportUrls
-                      && exportUrls.exportDetectionsUrlTrackJSON })"                >
+                    && exportUrls.exportDetectionsUrlTrackJSON })"
+                >
                   <span
                     v-if="exportUrls.exportDetectionsUrl"
                   >DIVE TrackJSON</span>
                   <span
                     v-else
                   >detections unavailable</span>
-                      </v-btn>
-            <!-- <v-btn
+                </v-btn>
+                <!-- <v-btn
               depressed
               block
               :disabled="!exportUrls.exportDetectionsUrl"
@@ -336,7 +337,7 @@ export default defineComponent({
               <span v-if="exportUrls.exportDetectionsUrl">annotations</span>
               <span v-else>detections unavailable</span>
             </v-btn> -->
-            </v-col>
+              </v-col>
             </v-row>
           </v-card-actions>
 

server/dive_server/crud_rpc.py

@@ -288,7 +288,7 @@ def run_training(
 def _get_data_by_type(
     file: types.GirderModel,
     image_map: Optional[Dict[str, int]] = None,
-) -> Optional[GetDataReturnType]:
+) -> Optional[Tuple[GetDataReturnType, Optional[List[str]]]]:
     """
     Given an arbitrary Girder file model, figure out what kind of file it is and
     parse it appropriately.
@@ -325,10 +325,10 @@ def _get_data_by_type(
 
     # Parse the file as the now known type
     if as_type == crud.FileType.VIAME_CSV:
-        converted, attributes = viame.load_csv_as_tracks_and_attributes(
+        converted, attributes, warnings = viame.load_csv_as_tracks_and_attributes(
             file_string.splitlines(), image_map
         )
-        return {'annotations': converted, 'meta': None, 'attributes': attributes, 'type': as_type}
+        return {'annotations': converted, 'meta': None, 'attributes': attributes, 'type': as_type}, warnings
     if as_type == crud.FileType.MEVA_KPF:
         converted, attributes = kpf.convert(kpf.load(file_string))
         return {'annotations': converted, 'meta': None, 'attributes': attributes, 'type': as_type}
@@ -374,6 +374,7 @@ def process_items(
         folder,
         user,
     )
+    aggregate_warnings = []
     for item in unprocessed_items:
         file: Optional[types.GirderModel] = next(Item().childFiles(item), None)
         if file is None:
@@ -383,7 +384,9 @@ def process_items(
             image_map = None
             if fromMeta(folder, constants.TypeMarker) == 'image-sequence':
                 image_map = crud.valid_image_names_dict(crud.valid_images(folder, user))
-            results = _get_data_by_type(file, image_map=image_map)
+            results, warnings = _get_data_by_type(file, image_map=image_map)
+            if warnings:
+                aggregate_warnings += warnings
         except Exception as e:
             Item().remove(item)
             raise RestException(f'{file["name"]} was not a supported file type: {e}') from e
@@ -414,7 +417,7 @@ def process_items(
             crud.saveImportAttributes(folder, results['attributes'], user)
         if results['meta']:
             crud_dataset.update_metadata(folder, results['meta'], False)
-
+    return aggregate_warnings
 
 def postprocess(
     user: types.GirderUserModel,
@@ -424,7 +427,7 @@ def postprocess(
     additive=False,
     additivePrepend='',
     set='',
-) -> types.GirderModel:
+) -> Tuple[types.GirderModel, Optional[List[str]]]:
     """
     Post-processing to be run after media/annotation import
 
@@ -539,8 +542,8 @@ def postprocess(
 
         Folder().save(dsFolder)
 
-    process_items(dsFolder, user, additive, additivePrepend, set)
-    return dsFolder
+    aggregate_warnings = process_items(dsFolder, user, additive, additivePrepend, set)
+    return dsFolder, aggregate_warnings
 
 
 def convert_large_image(