Automation7
Industrial Vision · UK
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// TOMATO AI INSPECTOR — LIVE DEMO

TOMATO INSPECTOR

Real-time defect detection and ripeness grading to optimize harvest selection and export compliance. Our Neural Inference Engine identifies 12+ categories of pathologies and phenological stages with surgical precision.

High-Speed Neural Inference Multi-Class Classification (12+ Categories) 97.1% Detection Accuracy Real-Time Edge Processing Demo Active
97.1%
Operational Reliability
Precision in high-speed sorting
12+
Detection Categories
Pathologies, ripeness & debris
< 100ms
Latency Per Unit
Local Edge processing
15K+
Proprietary Dataset
Export-grade curated samples

Live Scan Gallery

SCAN_0001
Tomato scan 1
half_ripe ripe ×3 unripe ×3
Mixed Ripeness
7 detections · conf ≥ 0.25
SCAN_0002
Tomato scan 2
brown_rugose ×3 ripe ×11
Disease Detected
3 detections · REJECT
SCAN_0003
Tomato scan 3
anthracnose ×2 rotten ×1
Defects Found
4 detections · ALERT
SCAN_0004
Tomato scan 4
ripe ×4
Premium Quality
4 detections · APPROVED
SCAN_0005
Tomato scan 5
half_ripe ×1 ripe ×5
Near Ripe
6 detections · MONITOR
SCAN_0006
Tomato scan 6
unripe ×5
Unripe Lot
5 detections · HOLD

// CLICK ANY IMAGE TO EXPAND — REAL MODEL OUTPUT — NO FILTERS APPLIED

What We Detect

Ripe

Optimal harvest condition. Ready for market or processing.

mAP50 89.8%

Unripe

Green, not ready. Requires additional maturation time.

mAP50 89.3%

Early Maturity (Unripe/Half-Ripe)

Transitional stage. Separate for delayed distribution routes.

mAP50 80.7%

Rotten

Decomposition detected. Immediate rejection required.

mAP50 72.0%

Mold

Fungal growth present. Cross-contamination risk.

mAP50 82.8%

Anthracnose

Fungal disease causing sunken lesions. Quarantine protocol.

mAP50 61.4%

Fruit Cracking

Physical damage from irregular watering. Reduces shelf life.

mAP50 70.8%

Brown Rugose

Viral disease. Highly contagious — full lot inspection required.

mAP50 50.0%

Blossom End Rot

Calcium deficiency disorder. Not contagious but reduces value.

mAP50 76.1%

Sunscald

Sun damage causing white/yellow patches. Cosmetic defect.

mAP50 44.8%

Inspection Process

01

Capture

Image acquisition via industrial vision sensors, IP cameras, or mobile devices. No specialized environment required.

02

Analysis

The Neural Engine processes the data in milliseconds, localizing and classifying every individual fruit.

03

Verdict

The system issues an autonomous decision (Approve / Monitor / Reject) based on your specific quality thresholds.

04

Traceability

Automated generation of batch quality reports (PDF/CSV) for audit trails and export documentation.

TEST THE SYSTEM WITH
YOUR OWN CROP

Upload your own photos — use images from your current lot for a real-world test

Live detection results — see bounding boxes and classifications in real time

Downloadable PDF report — keep a sample quality report from your own data

No installation required — runs fully in the browser, any device

REQUEST_DEMO_ACCESS

Want to validate our technology using real data from your facility? Follow these steps to activate your dedicated processing instance:

REQUEST

Email us at contacto@thepezgroup.com with the subject line:
"DEMO — [Your Company Name]"

ACTIVATION

We will provide a secure link and unique credentials for your organisation within 24 hours.

EXECUTION

Upload your own batch photos and receive instant AI analysis with a full downloadable technical report — Free of charge.

Data Security Note: To ensure peak performance and data privacy, we activate isolated processing instances for every client. Your production data remains strictly confidential and is not shared.

READY TO AUTOMATE YOUR QUALITY CONTROL?

We provide a technical proof-of-concept using your specific product samples and line conditions. No commitment required.