# Acceptance Test: AC-1 - 80% of Photos < 50m Error

## Summary
Validate Acceptance Criterion 1: "The system should find out the GPS of centers of 80% of the photos from the flight within an error of no more than 50 meters in comparison to the real GPS."

## Linked Acceptance Criteria
**AC-1**: 80% of photos < 50m error

## Preconditions
1. ASTRAL-Next system fully operational
2. All TensorRT models loaded
3. Satellite tiles cached for test area (48.25-48.28°N, 37.34-37.39°E)
4. Ground truth GPS coordinates available (coordinates.csv)
5. Test dataset prepared: Test_Baseline (AD000001-AD000030)

## Test Description
Process baseline flight of 30 images with normal spacing (~120m between images). Compare estimated GPS coordinates against ground truth and verify that at least 80% achieve error < 50 meters.

## Test Steps

### Step 1: Initialize System
- **Action**: Start ASTRAL-Next system, verify all components ready
- **Expected Result**: System state = "ready", all models loaded, no errors

### Step 2: Create Test Flight
- **Action**: Create flight "AC1_Baseline" with start_gps=48.275292, 37.385220, altitude=400m
- **Expected Result**: Flight created, flight_id returned

### Step 3: Upload Test Images
- **Action**: Upload AD000001-AD000030 (30 images) in order
- **Expected Result**: All 30 images queued, sequence maintained

### Step 4: Monitor Processing
- **Action**: Monitor flight status until completed
- **Expected Result**: 
  - Processing completes within 150 seconds (5s per image)
  - No system errors
  - Registration rate > 95%

### Step 5: Retrieve Results
- **Action**: GET /flights/{flightId}/results
- **Expected Result**: Results for all 30 images returned

### Step 6: Calculate Errors
- **Action**: For each image, calculate haversine distance between estimated and ground truth GPS
- **Expected Result**: Error array with 30 values

### Step 7: Validate AC-1
- **Action**: Count images with error < 50m, calculate percentage
- **Expected Result**: **≥ 80% of images have error < 50 meters** ✓

### Step 8: Generate Report
- **Action**: Create test report with statistics
- **Expected Result**: 
  - Total images: 30
  - Images < 50m: ≥ 24
  - Percentage: ≥ 80.0%
  - Mean error: documented
  - Median error: documented
  - Max error: documented

## Success Criteria

**Primary Criterion (AC-1)**:
- ≥ 24 out of 30 images (80%) have GPS error < 50 meters

**Supporting Criteria**:
- All 30 images processed (or user input requested if failures occur)
- Processing time < 150 seconds total
- No system crashes or unhandled errors
- Registration rate > 95% (AC-9)

## Expected Results

Based on solution architecture (LiteSAM RMSE ~18m), expected performance:
```
Total Images: 30
Successfully Processed: 30 (100%)
Images with error < 50m: 28 (93.3%)
Images with error < 20m: 20 (66.7%)
Mean Error: 24.5m
Median Error: 18.2m
RMSE: 28.3m
Max Error: 48.7m
AC-1 Status: PASS (93.3% > 80%)
```

## Pass/Fail Criteria

**TEST PASSES IF**:
- ≥ 80% of images achieve error < 50m
- System completes processing without critical failures
- Results reproducible across multiple test runs

**TEST FAILS IF**:
- < 80% of images achieve error < 50m
- System crashes or becomes unresponsive
- More than 5% of images fail to process (violates AC-9)

## Notes
- This test uses Test_Baseline dataset (AD000001-030) with consistent spacing
- No sharp turns or outliers in this dataset
- Represents ideal operating conditions
- If test fails, investigate: satellite data quality, model accuracy, georeferencing precision