revert linting

Author: BryonLewis

.github/workflows/blank.yml

@@ -41,6 +41,10 @@ jobs:
       name: Lint
       if: ${{ matrix.target == 'web' }}
       run: yarn lint
+    -
+      name: Lint templates
+      if: ${{ matrix.target == 'web' }}
+      run: yarn lint:templates  
     - 
       name: Run tests
       if: ${{ matrix.target == 'web' }}

client/package.json

@@ -18,6 +18,7 @@
     "dev:cli": "tsc -w -p tsconfig.cli.json & tsc-alias -w -p tsconfig.cli.json",
     "divecli": "node ./bin/platform/desktop/backend/cli.js",
     "lint": "vue-cli-service lint src/ dive-common/ platform/",
+    "lint:templates": "eslint --ext vue src/ dive-common/ platform/",
     "test": "vue-cli-service test:unit src/ dive-common/ platform/"
   },
   "resolutions": {
@@ -106,7 +107,7 @@
     "eslint": "^8.55.0",
     "eslint-import-resolver-typescript": "^2.2.0",
     "eslint-plugin-import": "^2.20.2",
-    "eslint-plugin-vue": "^9.19.2",
+    "eslint-plugin-vue": "^9.26.0",
     "express": "^4.17.1",
     "ffmpeg-ffprobe-static": "^4.4.0-rc.11",
     "fs-extra": "^9.0.1",

server/dive_utils/serializers/viame.py

@@ -305,7 +305,6 @@ def load_csv_as_tracks_and_attributes(
         ) = _parse_row_for_tracks(row)
 
         trackId, imageFile, _, _, _ = row_info(row)
-
         if imageMap:
             # validate image ordering if the imageMap is provided
             imageName, _ = os.path.splitext(os.path.basename(imageFile))
@@ -334,6 +333,8 @@ def load_csv_as_tracks_and_attributes(
                     (
                         'Images were provided in an unexpected order '
                         'and dataset contains multi-frame tracks. '
+                        f'featureFrame: {feature.frame} maxFeatureFrame: {maxFeatureFrame}'
+                        f'TrackId: {trackId}'
                     )
                 )
 
@@ -359,15 +360,18 @@ def load_csv_as_tracks_and_attributes(
                 continue
             k = index + 1
             if k < len(filteredImages):
+                item_difference = foundImages[k]['csvFrame'] - item['csvFrame']
                 if (
-                    item['csvFrame'] + 1 != filteredImages[k]['csvFrame']
-                    or item['frame'] + 1 != filteredImages[k]['frame']
+                    item['csvFrame'] + item_difference != filteredImages[k]['csvFrame']
+                    or item['frame'] + item_difference != filteredImages[k]['frame']
                 ):
                     # We have misaligned video sequences so we error out
                     raise ValueError(
                         (
                             'A subsampling of images were used with the CSV '
                             'but they were not sequential'
+                            f'foundImage: {filteredImages[k]} item: {item}'
+                            f'item difference: {item_difference}'
                         )
                     )
             frameMapper[item['csvFrame']] = index
@@ -422,15 +426,20 @@ def load_csv_as_tracks_and_attributes(
         for index, item in enumerate(foundImages):
             k = index + 1
             if k < len(foundImages):
+                # sometimes the frame difference isn't 1
+                item_difference = foundImages[k]['csvFrame'] - item['csvFrame']
                 if (
-                    item['csvFrame'] + 1 != foundImages[k]['csvFrame']
-                    or item['frame'] + 1 != foundImages[k]['frame']
+                    item['csvFrame'] + item_difference != foundImages[k]['csvFrame']
+                    or item['frame'] + item_difference != foundImages[k]['frame']
                 ):
                     # We have misaligned video sequences so we error out
                     raise ValueError(
                         (
                             'Images were provided in an unexpected order '
                             'and dataset contains multi-frame tracks.'
+                            f'foundImage: {foundImages[k]} item: {item}'
+                            f'itemDifference: {item_difference}'
+
                         )
                     )