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README.md

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+---
+tags:
+- Image Classification
+- Object Detection
+- Behavior Recognition
+- Express Logistics
+- Forklift Operations Management
+- Warehouse Management
+license: cc-by-nc-sa-4.0
+task_categories:
+- image-classification
+language:
+- en
+pretty_name: Forklift Loading/Unloading Operations Status Detection Image Dataset
+size_categories:
+- 1B<n<10B
+---
+
+# Forklift Loading/Unloading Operations Status Detection Image Dataset
+
+Driven by globalization and the rise of e-commerce, the express logistics industry demands fast, safe, and efficient operational processes. Current loading and unloading operation management mainly relies on manual monitoring and experience judgment, facing challenges such as misjudgment, high risk, and inefficiency. Existing image recognition solutions perform poorly in complex warehouse environments, especially in recognizing diverse forklift operation statuses. This dataset aims to improve the accuracy of operational status recognition during forklift loading and unloading processes by addressing visual perception and environmental adaptability issues through large-scale data training. Data collection uses high-resolution industrial cameras, covering different lighting conditions during day and night to ensure comprehensiveness. The data has undergone multiple rounds of quality control, including annotation consistency checks and reviews by professional warehousing and logistics experts. The annotation team comprises more than 50 logistics industry experts and data scientists. Data preprocessing includes image denoising, contrast enhancement, and size normalization. Data is organized and stored in JPG format, with structured file naming and classification labels.
+
+## Technical Specifications
+
+| Field | Type | Description |
+| :---  | :---  | :--- |
+| file_name | string | File name |
+| quality | string | Resolution |
+| forklift_type | string | Identifies the model of the forklift appearing in the image. |
+| operator_presence | boolean | Indicates whether an operator is present in the image. |
+| load_type | string | Identifies the type of load carried by the forklift in the image (e.g., boxes, pallets). |
+| operation_status | string | Indicates the current operational status of the forklift in the image (e.g., loading, unloading, idle). |
+| safety_gear | boolean | Determines whether the operator is wearing safety gear (e.g., helmet, reflective vest). |
+| environment_condition | string | Describes the conditions of the environment in which the operation is taking place (e.g., indoor, outdoor, lighting conditions). |
+| collision_risk | boolean | Identifies potential collision risks involving the forklift in the image. |
+
+## Compliance Statement
+
+<table>
+  <tr>
+    <td>Authorization Type</td>
+    <td>CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)</td>
+  </tr>
+  <tr>
+    <td>Commercial Use</td>
+    <td>Requires exclusive subscription or authorization contract (monthly or per-invocation charging)</td>
+  </tr>
+  <tr>
+    <td>Privacy and Anonymization</td>
+    <td>No PII, no real company names, simulated scenarios follow industry standards</td>
+  </tr>
+  <tr>
+    <td>Compliance System</td>
+    <td>Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs</td>
+  </tr>
+</table>
+
+## Source & Contact
+
+If you need more dataset details, please visit [Mobiusi](https://www.mobiusi.com/datasets/dee2b81fdd2252c15634a9e88fe78085?utm_source=huggingface&utm_medium=referral). or contact us via contact@mobiusi.com