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graphs/graph_data.json

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+    0.6000000000000001,
+    0.7000000000000001,
+    0.8,
+    0.9,
+    1,
+    1.1,
+    1.2000000000000002,
+    1.3,
+    1.4000000000000001,
+    1.5,
+    1.6,
+    1.7000000000000002,
+    1.8,
+    1.9000000000000001,
+    2,
+    2.1,
+    2.2,
+    2.3000000000000003,
+    2.4000000000000004,
+    2.5,
+    2.6,
+    2.7,
+    2.8000000000000003,
+    2.9000000000000004,
+    3,
+    3.1,
+    3.2,
+    3.3000000000000003,
+    3.4000000000000004,
+    3.5,
+    3.6,
+    3.7,
+    3.8000000000000003,
+    3.9000000000000004,
+    4,
+    4.1000000000000005,
+    4.2,
+    4.3,
+    4.4,
+    4.5,
+    4.6000000000000005,
+    4.7,
+    4.800000000000001,
+    4.9,
+    5,
+    5.1000000000000005,
+    5.2,
+    5.300000000000001,
+    5.4,
+    5.5,
+    5.6000000000000005,
+    5.7,
+    5.800000000000001,
+    5.9,
+    6,
+    6.1000000000000005,
+    6.2,
+    6.300000000000001,
+    6.4,
+    6.5,
+    6.6000000000000005,
+    6.7,
+    6.800000000000001,
+    6.9,
+    7,
+    7.1000000000000005,
+    7.2,
+    7.300000000000001,
+    7.4,
+    7.5,
+    7.6000000000000005,
+    7.7,
+    7.800000000000001,
+    7.9,
+    8,
+    8.1,
+    8.200000000000001,
+    8.3,
+    8.4,
+    8.5,
+    8.6,
+    8.700000000000001,
+    8.8,
+    8.9,
+    9,
+    9.1,
+    9.200000000000001,
+    9.3,
+    9.4,
+    9.5,
+    9.600000000000001,
+    9.700000000000001,
+    9.8,
+    9.9,
+    10,
+    10.100000000000001,
+    10.200000000000001,
+    10.3,
+    10.4,
+    10.5,
+    10.600000000000001,
+    10.700000000000001,
+    10.8,
+    10.9,
+    11,
+    11.100000000000001,
+    11.200000000000001,
+    11.3,
+    11.4,
+    11.5,
+    11.600000000000001,
+    11.700000000000001,
+    11.8,
+    11.9,
+    12,
+    12.100000000000001,
+    12.200000000000001,
+    12.3,
+    12.4,
+    12.5,
+    12.600000000000001,
+    12.700000000000001,
+    12.8,
+    12.9,
+    13,
+    13.100000000000001,
+    13.200000000000001,
+    13.3,
+    13.4,
+    13.5,
+    13.600000000000001,
+    13.700000000000001,
+    13.8,
+    13.9,
+    14,
+    14.100000000000001,
+    14.200000000000001,
+    14.3,
+    14.4,
+    14.5,
+    14.600000000000001,
+    14.700000000000001,
+    14.8,
+    14.9,
+    15,
+    15.100000000000001,
+    15.200000000000001,
+    15.3,
+    15.4,
+    15.5,
+    15.600000000000001,
+    15.700000000000001,
+    15.8,
+    15.9,
+    16,
+    16.1,
+    16.2,
+    16.3,
+    16.400000000000002,
+    16.5,
+    16.6,
+    16.7,
+    16.8,
+    16.900000000000002,
+    17,
+    17.1,
+    17.2,
+    17.3,
+    17.400000000000002,
+    17.5,
+    17.6,
+    17.7,
+    17.8,
+    17.900000000000002,
+    18,
+    18.1,
+    18.2,
+    18.3,
+    18.400000000000002,
+    18.5,
+    18.6,
+    18.7,
+    18.8,
+    18.900000000000002,
+    19,
+    19.1,
+    19.200000000000003,
+    19.3,
+    19.400000000000002,
+    19.5,
+    19.6,
+    19.700000000000003,
+    19.8,
+    19.900000000000002,
+    20,
+    20.1,
+    20.200000000000003,
+    20.3,
+    20.400000000000002,
+    20.5,
+    20.6,
+    20.700000000000003,
+    20.8,
+    20.900000000000002,
+    21,
+    21.1,
+    21.200000000000003,
+    21.3,
+    21.400000000000002,
+    21.5,
+    21.6,
+    21.700000000000003,
+    21.8,
+    21.900000000000002,
+    22,
+    22.1,
+    22.200000000000003,
+    22.3,
+    22.400000000000002,
+    22.5,
+    22.6,
+    22.700000000000003,
+    22.8,
+    22.900000000000002,
+    23,
+    23.1,
+    23.200000000000003,
+    23.3,
+    23.400000000000002,
+    23.5,
+    23.6,
+    23.700000000000003,
+    23.8,
+    23.900000000000002,
+    24,
+    24.1,
+    24.200000000000003,
+    24.3,
+    24.400000000000002,
+    24.5,
+    24.6,
+    24.700000000000003,
+    24.8,
+    24.900000000000002,
+    25,
+    25.1,
+    25.200000000000003,
+    25.3,
+    25.400000000000002,
+    25.5,
+    25.6,
+    25.700000000000003,
+    25.8,
+    25.900000000000002,
+    26,
+    26.1,
+    26.200000000000003,
+    26.3,
+    26.400000000000002,
+    26.5,
+    26.6,
+    26.700000000000003,
+    26.8,
+    26.900000000000002,
+    27,
+    27.1,
+    27.200000000000003,
+    27.3,
+    27.400000000000002,
+    27.5,
+    27.6,
+    27.700000000000003,
+    27.8,
+    27.900000000000002,
+    28,
+    28.1,
+    28.200000000000003,
+    28.3,
+    28.400000000000002,
+    28.5,
+    28.6,
+    28.700000000000003,
+    28.8,
+    28.900000000000002,
+    29,
+    29.1,
+    29.200000000000003,
+    29.3,
+    29.400000000000002,
+    29.5,
+    29.6,
+    29.700000000000003,
+    29.8,
+    29.900000000000002
+  ],
+  "dataset_id": "wave_bender_graph_data"
+}

huggingface_loader.py

@@ -0,0 +1,72 @@
+#!/usr/bin/env python3
+"""
+Hugging Face Dataset Loader for WAVE BENDER IDE v5.0
+This script loads the dataset WITHOUT ArrowInvalid errors.
+"""
+
+import json
+from datasets import Dataset, DatasetDict
+import os
+
+def load_wave_bender_dataset(dataset_path):
+    """
+    Load WAVE BENDER dataset from extracted directory.
+    
+    Args:
+        dataset_path (str): Path to extracted dataset directory
+        
+    Returns:
+        DatasetDict: Dictionary of datasets
+    """
+    
+    datasets = {}
+    
+    # Load telemetry data
+    telemetry_file = os.path.join(dataset_path, "telemetry", "telemetry.jsonl")
+    if os.path.exists(telemetry_file):
+        datasets['telemetry'] = Dataset.from_json(telemetry_file)
+        print(f"Loaded telemetry data: {len(datasets['telemetry'])} records")
+    
+    # Load SLAM data
+    slam_path = os.path.join(dataset_path, "slam")
+    
+    obstacles_file = os.path.join(slam_path, "obstacles.json")
+    if os.path.exists(obstacles_file):
+        datasets['slam_obstacles'] = Dataset.from_json(obstacles_file)
+        print(f"Loaded SLAM obstacles: {len(datasets['slam_obstacles'])} records")
+    
+    detections_file = os.path.join(slam_path, "detections.json")
+    if os.path.exists(detections_file):
+        datasets['slam_detections'] = Dataset.from_json(detections_file)
+        print(f"Loaded SLAM detections: {len(datasets['slam_detections'])} records")
+    
+    avoidances_file = os.path.join(slam_path, "avoidances.json")
+    if os.path.exists(avoidances_file):
+        datasets['slam_avoidances'] = Dataset.from_json(avoidances_file)
+        print(f"Loaded SLAM avoidances: {len(datasets['slam_avoidances'])} records")
+    
+    # Load training data
+    stats_path = os.path.join(dataset_path, "statistics")
+    
+    epochs_file = os.path.join(stats_path, "epochs.json")
+    if os.path.exists(epochs_file):
+        datasets['training_epochs'] = Dataset.from_json(epochs_file)
+        print(f"Loaded training epochs: {len(datasets['training_epochs'])} records")
+    
+    summary_file = os.path.join(stats_path, "summary.json")
+    if os.path.exists(summary_file):
+        datasets['statistics'] = Dataset.from_json(summary_file)
+        print("Loaded statistics summary")
+    
+    # Create DatasetDict
+    dataset_dict = DatasetDict(datasets)
+    
+    print(f"\n✅ Dataset loaded successfully with {len(datasets)} components")
+    print("✅ No ArrowInvalid errors - all schemas are separate and consistent")
+    
+    return dataset_dict
+
+if __name__ == "__main__":
+    # Example usage
+    dataset = load_wave_bender_dataset("./extracted_dataset")
+    print(f"\nDataset structure: {list(dataset.keys())}")

metadata/README.md

@@ -0,0 +1,104 @@
+# WAVE BENDER IDE - Training Dataset
+
+## Dataset Overview
+Generated by WAVE BENDER IDE v5.0 - Web-based Drone Telemetry & SLAM Training Dataset Generator
+
+**📊 Dataset Statistics:**
+- **Total Telemetry Points**: 12,544
+- **Training Duration**: 125.4 seconds
+- **Sample Rate**: 100 Hz
+- **Training Epochs**: 0
+- **Obstacles Detected**: 2
+- **Avoidance Maneuvers**: 0
+- **Training Progress**: 8%
+
+## 🚀 Loading the Dataset in Hugging Face
+
+### CORRECT WAY - Load each dataset separately:
+```python
+from datasets import Dataset, DatasetDict
+import json
+
+# Load telemetry data (separate dataset)
+telemetry_dataset = Dataset.from_json("telemetry/telemetry.jsonl")
+
+# Load SLAM data (separate datasets)
+obstacles_dataset = Dataset.from_json("slam/obstacles.json")
+detections_dataset = Dataset.from_json("slam/detections.json")
+avoidances_dataset = Dataset.from_json("slam/avoidances.json")
+
+# Load training data (separate datasets)
+epochs_dataset = Dataset.from_json("statistics/epochs.json")
+stats_dataset = Dataset.from_json("statistics/summary.json")
+
+# Create DatasetDict with SEPARATE datasets (no schema conflicts!)
+dataset_dict = DatasetDict({
+    'telemetry': telemetry_dataset,
+    'slam_obstacles': obstacles_dataset,
+    'slam_detections': detections_dataset,
+    'slam_avoidances': avoidances_dataset,
+    'training_epochs': epochs_dataset,
+    'statistics': stats_dataset
+})
+```
+
+## ✅ NO ARROWINVALID ERRORS - Why this works:
+
+1. **Separate Files**: Each data type is in its own file with consistent schema
+2. **Separate Datasets**: Each file is loaded as a separate Dataset
+3. **No Schema Mixing**: Different schemas don't conflict because they're separate
+4. **Always Valid**: Empty arrays still have consistent schemas
+
+## 📁 Directory Structure
+```
+wave_bender_dataset.zip/
+├── telemetry/
+│   ├── telemetry.jsonl     # Telemetry data (JSON Lines)
+│   ├── telemetry.csv       # Telemetry data (CSV)
+│   └── telemetry_schema.json
+├── slam/
+│   ├── obstacles.json      # Obstacle definitions
+│   ├── detections.json     # Detection events
+│   ├── avoidances.json     # Avoidance maneuvers
+│   └── training_params.json
+├── statistics/
+│   ├── epochs.json         # Epoch progression
+│   └── summary.json        # Statistics summary
+├── graphs/
+│   └── graph_data.json
+├── metadata/
+│   ├── dataset_card.json
+│   └── README.md
+└── huggingface_loader.py
+```
+
+## 🎯 Training Configuration
+- **Complexity**: 7/10
+- **Noise Level**: 2.5/5
+- **Frequency**: 1.8 Hz
+- **Center Region Training**: Yes
+- **Dynamic Obstacles**: Yes
+- **Avoidance Training**: Yes
+
+## 🔧 Fixed ArrowInvalid Errors
+This export structure completely eliminates ArrowInvalid errors by:
+
+1. **Separating different schema types** into different directories
+2. **Never mixing schemas** in the same file
+3. **Always providing consistent schemas**, even for empty data
+4. **Using unique dataset_id fields** to prevent confusion
+
+## 📝 Citation
+```
+@dataset{wave_bender_dataset_2024,
+  title = {WAVE BENDER IDE v5.0 - Drone Telemetry & SLAM Training Dataset},
+  author = {webXOS},
+  year = {2024},
+  url = {https://huggingface.co/datasets/webxos/wave_bender_dataset},
+  note = {Synthetic dataset for drone autonomy training}
+}
+```
+
+---
+**Generated**: 2026-01-08T01:43:26.624Z
+**WAVE BENDER IDE v5.0** | **Hugging Face Compatible** | **ArrowInvalid Fixed**

metadata/dataset_card.json

@@ -0,0 +1,42 @@
+{
+  "language": [
+    "en"
+  ],
+  "license": "mit",
+  "annotations_creators": [
+    "machine-generated"
+  ],
+  "task_categories": [
+    "autonomous-driving",
+    "robot-navigation"
+  ],
+  "task_ids": [
+    "obstacle-avoidance",
+    "slam",
+    "drone-telemetry"
+  ],
+  "pretty_name": "WAVE BENDER Drone Telemetry & SLAM Dataset",
+  "dataset_info": {
+    "splits": {
+      "telemetry": 12544,
+      "slam_obstacles": 15,
+      "slam_detections": 2,
+      "slam_avoidances": 0,
+      "training_epochs": 0,
+      "statistics": 1
+    }
+  },
+  "size_categories": [
+    "10K<n<100K"
+  ],
+  "tags": [
+    "drone",
+    "telemetry",
+    "slam",
+    "obstacle-avoidance",
+    "synthetic-data",
+    "machine-learning",
+    "autonomous-systems"
+  ],
+  "dataset_id": "wave_bender_v5.0"
+}

slam/avoidances.json

@@ -0,0 +1 @@
+[]

slam/detections.json

@@ -0,0 +1,24 @@
+[
+  {
+    "detection_id": 8,
+    "timestamp": 0.2800000000000001,
+    "obstacle_id": 8,
+    "distance": 7.686493175491766,
+    "position_x": 2.9467292366225295,
+    "position_y": 18.4006364920203,
+    "position_z": 4.898250556236892,
+    "training_weight": 1.0978306555379476,
+    "dataset_id": "wave_bender_slam_detections"
+  },
+  {
+    "detection_id": 4,
+    "timestamp": 0.7900000000000005,
+    "obstacle_id": 4,
+    "distance": 7.93359589596902,
+    "position_x": -5.926440063314495,
+    "position_y": 19.27141286677167,
+    "position_z": 1.115351699999767,
+    "training_weight": 1.9993508839147773,
+    "dataset_id": "wave_bender_slam_detections"
+  }
+]

slam/obstacles.json

@@ -0,0 +1,137 @@
+[
+  {
+    "obstacle_id": 0,
+    "position_x": 12.376133814269295,
+    "position_y": 11.810452509586352,
+    "position_z": -6.68575507063982,
+    "type": "cone",
+    "training_weight": 2.902887775783297,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 1,
+    "position_x": 0.9073142956212654,
+    "position_y": 9.026231701385136,
+    "position_z": -12.630701838041391,
+    "type": "cylinder",
+    "training_weight": 1.9599556686520072,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 2,
+    "position_x": 12.109042477510524,
+    "position_y": 12.129719313639688,
+    "position_z": -14.547121518080605,
+    "type": "cone",
+    "training_weight": 2.2339019862377594,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 3,
+    "position_x": -6.7424254948383595,
+    "position_y": 12.588724284477419,
+    "position_z": -10.721413730262855,
+    "type": "sphere",
+    "training_weight": 2.9478283485709156,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 4,
+    "position_x": -5.926440063314495,
+    "position_y": 16.883188802852697,
+    "position_z": 1.115351699999767,
+    "type": "cube",
+    "training_weight": 1.9993508839147773,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 5,
+    "position_x": -3.094781698103266,
+    "position_y": 23.38401130409484,
+    "position_z": -12.2594886838797,
+    "type": "sphere",
+    "training_weight": 1.4061216953949403,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 6,
+    "position_x": 0.9217610562597678,
+    "position_y": 14.039436222294675,
+    "position_z": 11.262983471476279,
+    "type": "sphere",
+    "training_weight": 1.5197665072060251,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 7,
+    "position_x": 10.944571594573993,
+    "position_y": 24.22053856802599,
+    "position_z": 4.316861221292818,
+    "type": "sphere",
+    "training_weight": 2.6785305439462253,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 8,
+    "position_x": 2.9467292366225295,
+    "position_y": 15.496287537214732,
+    "position_z": 4.898250556236892,
+    "type": "sphere",
+    "training_weight": 1.0978306555379476,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 9,
+    "position_x": 5.5192474264972695,
+    "position_y": 22.176684419003166,
+    "position_z": 14.711074430934485,
+    "type": "cylinder",
+    "training_weight": 2.5313025101315736,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 10,
+    "position_x": -11.142678266655786,
+    "position_y": 23.295178109130354,
+    "position_z": -11.463811137657782,
+    "type": "cylinder",
+    "training_weight": 2.8033143455703855,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 11,
+    "position_x": -4.495005379191833,
+    "position_y": 15.326854650642183,
+    "position_z": 9.521789609301575,
+    "type": "cone",
+    "training_weight": 2.8281844004171632,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 12,
+    "position_x": 0.41791622330456635,
+    "position_y": 20.29041127991094,
+    "position_z": 13.798183182773016,
+    "type": "cone",
+    "training_weight": 2.1746916734941646,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 13,
+    "position_x": 6.094750756435062,
+    "position_y": 7.08062044775529,
+    "position_z": 10.774281876834143,
+    "type": "cube",
+    "training_weight": 2.0693231728971293,
+    "dataset_id": "wave_bender_slam_obstacles"
+  },
+  {
+    "obstacle_id": 14,
+    "position_x": 11.315299260472516,
+    "position_y": 10.563136770775227,
+    "position_z": -2.9243744483036513,
+    "type": "cube",
+    "training_weight": 2.4649052167314673,
+    "dataset_id": "wave_bender_slam_obstacles"
+  }
+]

slam/training_params.json

@@ -0,0 +1,10 @@
+{
+  "complexity": 7,
+  "noise": 2.5,
+  "frequency": 1.8,
+  "sample_rate": 100,
+  "center_region_training": true,
+  "dynamic_obstacles": true,
+  "avoidance_training": true,
+  "dataset_id": "wave_bender_training_params"
+}

statistics/epochs.json

@@ -0,0 +1,10 @@
+[
+  {
+    "epoch_number": 0,
+    "timestamp": 0,
+    "obstacles_detected": 0,
+    "avoidance_maneuvers": 0,
+    "training_progress": 0,
+    "dataset_id": "wave_bender_training_epochs"
+  }
+]

statistics/summary.json

@@ -0,0 +1,14 @@
+[
+  {
+    "total_points": 12544,
+    "obstacles_detected": 2,
+    "avoidance_maneuvers": 0,
+    "training_progress": 0.08,
+    "total_obstacles": 15,
+    "total_detections": 2,
+    "total_avoidances": 0,
+    "current_epoch": 1,
+    "generation_time": 125.37000000002723,
+    "dataset_id": "wave_bender_statistics_summary"
+  }
+]

telemetry/telemetry_schema.json

@@ -0,0 +1,16 @@
+{
+  "timestamp": "float64",
+  "acceleration_x": "float64",
+  "acceleration_y": "float64",
+  "acceleration_z": "float64",
+  "gyroscope_x": "float64",
+  "gyroscope_y": "float64",
+  "gyroscope_z": "float64",
+  "altitude": "float64",
+  "velocity": "float64",
+  "battery": "float64",
+  "temperature": "float64",
+  "gps_lat": "float64",
+  "gps_lon": "float64",
+  "signal_strength": "float64"
+}