Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
digest: string
kind: string
path: string
payload_sha3: string
prev: string
seq: int64
ts: timestamp[s]
project: string
licence: struct<spdx: string, class: string, source_file: null, redistribution_allowed: bool>
child 0, spdx: string
child 1, class: string
child 2, source_file: null
child 3, redistribution_allowed: bool
all_passed: bool
failed_ids: list<item: null>
child 0, item: null
metrics: struct<files_total: int64, source_files_scanned: int64, lines_of_code: int64, languages: struct<>>
child 0, files_total: int64
child 1, source_files_scanned: int64
child 2, lines_of_code: int64
child 3, languages: struct<>
sbom: struct<bomFormat: string, specVersion: string, serialNumber: string, version: int64, metadata: struc (... 272 chars omitted)
child 0, bomFormat: string
child 1, specVersion: string
child 2, serialNumber: string
child 3, version: int64
child 4, metadata: struct<timestamp: timestamp[s], component: struct<type: string, name: string, version: string, bom-r (... 146 chars omitted)
child 0, timestamp: timestamp[s]
child 1, component: struct<type: string, name: string, version: string, bom-ref: string, purl: string, licenses: list<it (... 41 chars omitted)
child 0, type: string
child 1, name: string
child 2, version: string
child 3, bom-ref: string
child 4, purl: string
child 5, licenses: list<item: struct<license: struct<id: string>>>
child 0, item: struc
...
m: null>>
child 0, count: int64
child 1, findings: list<item: null>
child 0, item: null
child 7, LLM08-VectorEmbeddingWeaknesses: struct<count: int64, findings: list<item: null>>
child 0, count: int64
child 1, findings: list<item: null>
child 0, item: null
child 8, LLM09-Misinformation: struct<count: int64, findings: list<item: null>>
child 0, count: int64
child 1, findings: list<item: null>
child 0, item: null
child 9, LLM10-UnboundedConsumption: struct<count: int64, findings: list<item: null>>
child 0, count: int64
child 1, findings: list<item: null>
child 0, item: null
schema: string
dependencies: struct<count: int64, unique: int64, by_ecosystem: struct<>, list: list<item: null>>
child 0, count: int64
child 1, unique: int64
child 2, by_ecosystem: struct<>
child 3, list: list<item: null>
child 0, item: null
source: struct<repo_path: string, git: struct<head: string, url: string, branch: string, committed_at: times (... 36 chars omitted)
child 0, repo_path: string
child 1, git: struct<head: string, url: string, branch: string, committed_at: timestamp[s], sha_verified_from: str (... 4 chars omitted)
child 0, head: string
child 1, url: string
child 2, branch: string
child 3, committed_at: timestamp[s]
child 4, sha_verified_from: string
passed: int64
blocker: string
failed: int64
to
{'schema': Value('string'), 'project': Value('string'), 'source': {'repo_path': Value('string'), 'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'committed_at': Value('timestamp[s]'), 'sha_verified_from': Value('string')}}, 'metrics': {'files_total': Value('int64'), 'source_files_scanned': Value('int64'), 'lines_of_code': Value('int64'), 'languages': {}}, 'licence': {'spdx': Value('string'), 'class': Value('string'), 'source_file': Value('null'), 'redistribution_allowed': Value('bool')}, 'dependencies': {'count': Value('int64'), 'unique': Value('int64'), 'by_ecosystem': {}, 'list': List(Value('null'))}, 'owasp_top10': {'total_findings': Value('int64'), 'files_with_findings': Value('int64'), 'severity': {'high': Value('int64'), 'medium': Value('int64'), 'low': Value('int64')}, 'categories': {'A01-BrokenAccessControl': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A02-CryptographicFailures': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A03-Injection': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A04-InsecureDesign': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A05-SecurityMisconfiguration': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A06-VulnerableComponents': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A07-AuthFailures': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A08-SoftwareDataIntegrity': {'count': Value('int64'), 'findings':
...
), 'findings': List(Value('null'))}, 'LLM02-SensitiveInfoDisclosure': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM03-SupplyChain': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM04-DataPoisoning': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM05-ImproperOutputHandling': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM06-ExcessiveAgency': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM07-SystemPromptLeak': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM08-VectorEmbeddingWeaknesses': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM09-Misinformation': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM10-UnboundedConsumption': {'count': Value('int64'), 'findings': List(Value('null'))}}}, 'sbom': {'bomFormat': Value('string'), 'specVersion': Value('string'), 'serialNumber': Value('string'), 'version': Value('int64'), 'metadata': {'timestamp': Value('timestamp[s]'), 'component': {'type': Value('string'), 'name': Value('string'), 'version': Value('string'), 'bom-ref': Value('string'), 'purl': Value('string'), 'licenses': List({'license': {'id': Value('string')}})}, 'properties': List({'name': Value('string'), 'value': Value('string')})}, 'components': List(Value('null'))}, 'elapsed_seconds': Value('float64'), 'all_passed': Value('bool'), 'passed': Value('int64'), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'blocker': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
digest: string
kind: string
path: string
payload_sha3: string
prev: string
seq: int64
ts: timestamp[s]
project: string
licence: struct<spdx: string, class: string, source_file: null, redistribution_allowed: bool>
child 0, spdx: string
child 1, class: string
child 2, source_file: null
child 3, redistribution_allowed: bool
all_passed: bool
failed_ids: list<item: null>
child 0, item: null
metrics: struct<files_total: int64, source_files_scanned: int64, lines_of_code: int64, languages: struct<>>
child 0, files_total: int64
child 1, source_files_scanned: int64
child 2, lines_of_code: int64
child 3, languages: struct<>
sbom: struct<bomFormat: string, specVersion: string, serialNumber: string, version: int64, metadata: struc (... 272 chars omitted)
child 0, bomFormat: string
child 1, specVersion: string
child 2, serialNumber: string
child 3, version: int64
child 4, metadata: struct<timestamp: timestamp[s], component: struct<type: string, name: string, version: string, bom-r (... 146 chars omitted)
child 0, timestamp: timestamp[s]
child 1, component: struct<type: string, name: string, version: string, bom-ref: string, purl: string, licenses: list<it (... 41 chars omitted)
child 0, type: string
child 1, name: string
child 2, version: string
child 3, bom-ref: string
child 4, purl: string
child 5, licenses: list<item: struct<license: struct<id: string>>>
child 0, item: struc
...
m: null>>
child 0, count: int64
child 1, findings: list<item: null>
child 0, item: null
child 7, LLM08-VectorEmbeddingWeaknesses: struct<count: int64, findings: list<item: null>>
child 0, count: int64
child 1, findings: list<item: null>
child 0, item: null
child 8, LLM09-Misinformation: struct<count: int64, findings: list<item: null>>
child 0, count: int64
child 1, findings: list<item: null>
child 0, item: null
child 9, LLM10-UnboundedConsumption: struct<count: int64, findings: list<item: null>>
child 0, count: int64
child 1, findings: list<item: null>
child 0, item: null
schema: string
dependencies: struct<count: int64, unique: int64, by_ecosystem: struct<>, list: list<item: null>>
child 0, count: int64
child 1, unique: int64
child 2, by_ecosystem: struct<>
child 3, list: list<item: null>
child 0, item: null
source: struct<repo_path: string, git: struct<head: string, url: string, branch: string, committed_at: times (... 36 chars omitted)
child 0, repo_path: string
child 1, git: struct<head: string, url: string, branch: string, committed_at: timestamp[s], sha_verified_from: str (... 4 chars omitted)
child 0, head: string
child 1, url: string
child 2, branch: string
child 3, committed_at: timestamp[s]
child 4, sha_verified_from: string
passed: int64
blocker: string
failed: int64
to
{'schema': Value('string'), 'project': Value('string'), 'source': {'repo_path': Value('string'), 'git': {'head': Value('string'), 'url': Value('string'), 'branch': Value('string'), 'committed_at': Value('timestamp[s]'), 'sha_verified_from': Value('string')}}, 'metrics': {'files_total': Value('int64'), 'source_files_scanned': Value('int64'), 'lines_of_code': Value('int64'), 'languages': {}}, 'licence': {'spdx': Value('string'), 'class': Value('string'), 'source_file': Value('null'), 'redistribution_allowed': Value('bool')}, 'dependencies': {'count': Value('int64'), 'unique': Value('int64'), 'by_ecosystem': {}, 'list': List(Value('null'))}, 'owasp_top10': {'total_findings': Value('int64'), 'files_with_findings': Value('int64'), 'severity': {'high': Value('int64'), 'medium': Value('int64'), 'low': Value('int64')}, 'categories': {'A01-BrokenAccessControl': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A02-CryptographicFailures': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A03-Injection': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A04-InsecureDesign': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A05-SecurityMisconfiguration': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A06-VulnerableComponents': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A07-AuthFailures': {'count': Value('int64'), 'findings': List(Value('null'))}, 'A08-SoftwareDataIntegrity': {'count': Value('int64'), 'findings':
...
), 'findings': List(Value('null'))}, 'LLM02-SensitiveInfoDisclosure': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM03-SupplyChain': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM04-DataPoisoning': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM05-ImproperOutputHandling': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM06-ExcessiveAgency': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM07-SystemPromptLeak': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM08-VectorEmbeddingWeaknesses': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM09-Misinformation': {'count': Value('int64'), 'findings': List(Value('null'))}, 'LLM10-UnboundedConsumption': {'count': Value('int64'), 'findings': List(Value('null'))}}}, 'sbom': {'bomFormat': Value('string'), 'specVersion': Value('string'), 'serialNumber': Value('string'), 'version': Value('int64'), 'metadata': {'timestamp': Value('timestamp[s]'), 'component': {'type': Value('string'), 'name': Value('string'), 'version': Value('string'), 'bom-ref': Value('string'), 'purl': Value('string'), 'licenses': List({'license': {'id': Value('string')}})}, 'properties': List({'name': Value('string'), 'value': Value('string')})}, 'components': List(Value('null'))}, 'elapsed_seconds': Value('float64'), 'all_passed': Value('bool'), 'passed': Value('int64'), 'failed': Value('int64'), 'failed_ids': List(Value('null')), 'blocker': Value('string')}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
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Check out the documentation for more information.
SMART_BIN
Anticloud offline package — upstream: nsankethreddy/SMART-BIN @
master.
What This Project Does
This project automates the task of waste segregation in public dustbins by classifying waste as either recyclable or non-recyclable.
Topics: dustbins, image-classification, image-processing, iot, raspberry-pi, real-time, waste-management-system, waste-segregation
Upstream README
Smart-Bins
Description
This project automates the task of waste segregation in public dustbins by classifying waste as either recyclable or non-recyclable. We use a Raspberry Pi along with a servo motor, IR, Ultra-Sonic Sensor, Pi Cam and a server(laptop) to accomplish the project.
The project has been implemented as an IoT system which captures images through the Pi and sends it to a server for processing. On the server, we use CNNs for the Machine learning/Image processing algorithms, which are used to identify type of waste that was dumped. The server communicates back to the Pi and the Pi actuates accordingly by turning the servo motor and thus dumping the garbage to either the recyclable or non-recyclable side. We use an ultrasonic sensor to detect the level of garbage accumalated in the bin.
If the bin has been filled, we use Twilio's API to send out a message, informing that the bin is full and has to be replaced.
File Placement
- Files to be placed in Raspberry Pi are in
PI/ - Files to be placed in the Server are in
SERVER/ - Files for Web Server (Frontend) are placed in
CLIENT/ - Directory structures are mentioned within
location.mdfor all Pi, Server and Web Server.
Requirements
- Tensorflow
- Keras
- SSH along with key setup between Pi and Server
- Python3
- Twilio credentials and libraries
How to run
- Setup directories according to each
location.md - Run
python3 ir.pyfrom the home directory in the pi. Machine Learning Model is in Server along with trained weights.
Results
- The model when trained for 200 epochs gave us 89% accuracy.
Credits
License
Upstream terms preserved in THIRD_PARTY_LICENSES/. Overlay licensed under Anticommons 0.1.0.
Verification
Recompute the SHA3-256 of BENCH.json and compare to this package’s register. Any drift = invalid package.
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