hoàn thành chức năng remove cloud train
This commit is contained in:
Victor Phan
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#!/usr/bin/env python3
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"""
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Test Cloud Removal Model Upload Feature
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"""
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import requests
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import json
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from pathlib import Path
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# API base URL
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BASE_URL = "http://localhost:8000"
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def test_upload_cloud_model(file_path):
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"""Test uploading a cloud removal model"""
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print(f"\n{'='*60}")
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print("TEST 1: Upload Cloud Removal Model")
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print(f"{'='*60}")
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if not Path(file_path).exists():
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print(f"❌ File not found: {file_path}")
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print(" Create a dummy .pth file for testing:")
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print(f" touch {file_path}")
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return None
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with open(file_path, 'rb') as f:
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files = {'file': (Path(file_path).name, f, 'application/octet-stream')}
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print(f"📤 Uploading: {file_path}")
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response = requests.post(f"{BASE_URL}/api/cloud-removal/upload", files=files)
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if response.status_code == 200:
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result = response.json()
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print(f"✅ Upload successful!")
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print(f" Filename: {result['filename']}")
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print(f" Size: {result['size_mb']} MB")
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print(f" Path: {result['path']}")
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return result['filename']
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else:
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print(f"❌ Upload failed: {response.status_code}")
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print(f" {response.json().get('detail', 'Unknown error')}")
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return None
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def test_list_cloud_models():
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"""Test listing cloud removal models"""
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print(f"\n{'='*60}")
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print("TEST 2: List Cloud Removal Models")
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print(f"{'='*60}")
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response = requests.get(f"{BASE_URL}/api/cloud-removal/models")
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if response.status_code == 200:
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data = response.json()
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print(f"✅ Found {data['count']} models:")
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for i, model in enumerate(data['models'], 1):
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print(f"\n {i}. {model['filename']}")
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print(f" Size: {model['size_mb']} MB")
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print(f" Created: {model['created']}")
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if 'epoch' in model:
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print(f" Epoch: {model['epoch']}, Val Loss: {model['val_loss']:.4f}")
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return data['models']
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else:
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print(f"❌ Failed to list models: {response.status_code}")
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return []
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def test_prediction_with_cloud_model(model_filename, cloud_model_filename):
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"""Test prediction using uploaded cloud removal model"""
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print(f"\n{'='*60}")
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print("TEST 3: Prediction with Custom Cloud Removal Model")
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print(f"{'='*60}")
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config = {
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"model_filename": model_filename,
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"min_lon": 105.80,
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"min_lat": 10.00,
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"max_lon": 105.82,
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"max_lat": 10.02,
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"start_date": "2024-01-15",
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"end_date": "2024-01-17",
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"max_scenes": 2,
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"cloud_cover": 30,
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"resolution": 20,
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"use_gpu": False,
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"export_ndvi": True,
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"export_classification": True,
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"cloud_removal_method": "deep",
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"cloud_removal_model": cloud_model_filename
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}
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print("📊 Prediction Config:")
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print(json.dumps(config, indent=2))
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print(f"\n🚀 Starting prediction with cloud removal model: {cloud_model_filename}")
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response = requests.post(
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f"{BASE_URL}/api/predict/with-ndvi",
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json=config,
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headers={'Content-Type': 'application/json'}
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)
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if response.status_code == 200:
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result = response.json()
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print(f"✅ Prediction started!")
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print(f" Message: {result.get('message')}")
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return result
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else:
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print(f"❌ Prediction failed: {response.status_code}")
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print(f" {response.json().get('detail', 'Unknown error')}")
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return None
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def test_delete_cloud_model(filename):
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"""Test deleting a cloud removal model"""
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print(f"\n{'='*60}")
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print("TEST 4: Delete Cloud Removal Model")
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print(f"{'='*60}")
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print(f"🗑️ Deleting: {filename}")
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response = requests.delete(f"{BASE_URL}/api/cloud-removal/models/{filename}")
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if response.status_code == 200:
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result = response.json()
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print(f"✅ {result['message']}")
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return True
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else:
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print(f"❌ Delete failed: {response.status_code}")
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return False
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def main():
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print("="*60)
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print("CLOUD REMOVAL MODEL UPLOAD - FEATURE TEST")
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print("="*60)
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# Test file path (create a dummy file for testing)
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test_file = "test_cloud_removal_model.pth"
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# Create dummy file if it doesn't exist
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if not Path(test_file).exists():
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print(f"\n📝 Creating dummy test file: {test_file}")
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Path(test_file).write_bytes(b"dummy_pytorch_model_data")
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# Run tests
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uploaded_filename = test_upload_cloud_model(test_file)
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if uploaded_filename:
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models = test_list_cloud_models()
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# Test prediction (requires a real land classification model)
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print(f"\n{'='*60}")
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print("NOTE: Prediction test requires a trained land classification model")
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print(" Skipping prediction test in this demo")
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print(f"{'='*60}")
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# Cleanup - delete test model
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if input("\nDelete test model? (y/n): ").lower() == 'y':
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test_delete_cloud_model(uploaded_filename)
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# Cleanup dummy file
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if Path(test_file).exists():
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Path(test_file).unlink()
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print(f"\n🗑️ Cleaned up dummy file: {test_file}")
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print(f"\n{'='*60}")
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print("TESTS COMPLETED")
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print(f"{'='*60}")
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if __name__ == "__main__":
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main()
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