Object Detection
TensorBoard
PyTorch
English
ultralytics
v8
ultralyticsplus
yolov8
yolo
vision
table detection
table extraction
table classification
document analysis
unstructured document
unstructured table extraction
structured table extraction
unstructured table detection
structured table detection
Eval Results
nehulagrawal
commited on
Commit
•
921daf1
1
Parent(s):
ee5f8f3
Update README.md
Browse files
README.md
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@@ -20,7 +20,7 @@ library_name: ultralytics
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library_version: 8.0.43
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inference: False
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model-index:
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-
- name: foduucom/table-detection-and-
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results:
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- task:
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type: object-detection
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@@ -33,7 +33,7 @@ language:
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metrics:
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- accuracy
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---
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Below is the Model Card for the YOLOv8s Table Detection and
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---
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@@ -110,7 +110,7 @@ pip install ultralyticsplus ultralytics
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from ultralyticsplus import YOLO, render_result
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# Load model
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model = YOLO('foduucom/table-detection-and-
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# Set model parameters
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model.overrides['conf'] = 0.25 # NMS confidence threshold
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@@ -169,7 +169,7 @@ For inquiries and contributions, please contact us at [email protected].
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@ModelCard{
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author = {Nehul Agrawal and
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Pranjal singh Thakur},
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title = { Table Detection and
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year = {2023}
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}
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```
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library_version: 8.0.43
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inference: False
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model-index:
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- name: foduucom/table-detection-and-extraction
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results:
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- task:
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type: object-detection
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metrics:
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- accuracy
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---
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Below is the Model Card for the YOLOv8s Table Detection and Extraction model:
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---
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from ultralyticsplus import YOLO, render_result
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# Load model
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model = YOLO('foduucom/table-detection-and-extraction')
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# Set model parameters
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model.overrides['conf'] = 0.25 # NMS confidence threshold
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@ModelCard{
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author = {Nehul Agrawal and
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Pranjal singh Thakur},
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title = { Table Detection and Extraction},
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year = {2023}
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}
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```
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