40f1e391
 tangwang
cnclip
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#!/usr/bin/env python3
"""
CN-CLIP 快速测试脚本
测试文本和图像编码功能
"""
from clip_client import Client
from sklearn.metrics.pairwise import cosine_similarity
import numpy as np
# 测试图片
TEST_IMAGE = "https://oss.essa.cn/98532128-cf8e-456c-9e30-6f2a5ea0c19f.jpg"
# 测试文本
TEST_TEXTS = [
"一只可爱的猫咪",
"美丽的高山风景",
"汽车在公路上行驶",
"现代建筑",
]
def test_connection():
"""测试服务连接"""
print("=" * 60)
print("测试 1: 连接服务")
print("=" * 60)
try:
client = Client('grpc://localhost:51000')
print("✓ 服务连接成功")
return client
except Exception as e:
print(f"✗ 连接失败: {e}")
print("\n请确保服务已启动:")
print(" ./scripts/start_cnclip_service.sh")
return None
def test_text_encoding(client):
"""测试文本编码"""
print("\n" + "=" * 60)
print("测试 2: 文本编码")
print("=" * 60)
print(f"\n测试文本:")
for i, text in enumerate(TEST_TEXTS, 1):
print(f" {i}. {text}")
try:
embeddings = client.encode(TEST_TEXTS)
print(f"\n✓ 文本编码成功")
print(f" 编码数量: {len(embeddings)}")
print(f" 向量形状: {embeddings.shape}")
print(f" 数据类型: {embeddings.dtype}")
print(f" 值域: [{embeddings.min():.4f}, {embeddings.max():.4f}]")
return embeddings
except Exception as e:
print(f"✗ 文本编码失败: {e}")
return None
def test_image_encoding(client):
"""测试图像编码"""
print("\n" + "=" * 60)
print("测试 3: 图像编码")
print("=" * 60)
print(f"\n测试图片: {TEST_IMAGE}")
try:
embeddings = client.encode([TEST_IMAGE])
print(f"\n✓ 图像编码成功")
print(f" 向量形状: {embeddings.shape}")
print(f" 数据类型: {embeddings.dtype}")
print(f" 值域: [{embeddings.min():.4f}, {embeddings.max():.4f}]")
return embeddings
except Exception as e:
print(f"✗ 图像编码失败: {e}")
return None
def test_image_text_retrieval(client, image_embedding, text_embeddings):
"""测试图文检索"""
print("\n" + "=" * 60)
print("测试 4: 图文检索（计算相似度）")
print("=" * 60)
print(f"\n使用图片搜索最匹配的文本...")
try:
# 计算相似度
similarities = cosine_similarity(image_embedding, text_embeddings)[0]
print(f"\n相似度排序:")
# 按相似度排序
sorted_indices = np.argsort(similarities)[::-1]
for rank, idx in enumerate(sorted_indices, 1):
text = TEST_TEXTS[idx]
score = similarities[idx]
bar = "█" * int(score * 50)
print(f" {rank}. {score:.4f} {bar} {text}")
print(f"\n最佳匹配: {TEST_TEXTS[sorted_indices[0]]}")
print(f"相似度分数: {similarities[sorted_indices[0]]:.4f}")
return similarities
except Exception as e:
print(f"✗ 相似度计算失败: {e}")
return None
def test_batch_encoding(client):
"""测试批量编码"""
print("\n" + "=" * 60)
print("测试 5: 批量编码性能")
print("=" * 60)
import time
# 准备测试数据
batch_texts = [f"测试文本 {i}" for i in range(50)]
print(f"\n编码 {len(batch_texts)} 条文本...")
try:
start = time.time()
embeddings = client.encode(batch_texts)
elapsed = time.time() - start
print(f"\n✓ 批量编码成功")
print(f" 耗时: {elapsed:.2f}秒")
print(f" 速度: {len(batch_texts)/elapsed:.2f} 条/秒")
print(f" 平均延迟: {elapsed/len(batch_texts)*1000:.2f}ms/条")
except Exception as e:
print(f"✗ 批量编码失败: {e}")
def main():
print("\n" + "=" * 60)
print("CN-CLIP 服务测试")
print("=" * 60)
print(f"\n测试图片: {TEST_IMAGE}")
print(f"服务地址: grpc://localhost:51000")
# 测试连接
client = test_connection()
if not client:
return
# 测试文本编码
text_embeddings = test_text_encoding(client)
if text_embeddings is None:
return
# 测试图像编码
image_embeddings = test_image_encoding(client)
if image_embeddings is None:
return
# 测试图文检索
test_image_text_retrieval(client, image_embeddings, text_embeddings)
# 测试批量编码性能
test_batch_encoding(client)
# 总结
print("\n" + "=" * 60)
print("测试总结")
print("=" * 60)
print("\n✓ 所有测试通过！")
print("\n服务运行正常，可以开始使用。")
print("\n下一步:")
print(" 1. 查看使用文档: cat docs/CNCLIP_USAGE_GUIDE.md")
print(" 2. 集成到你的项目")
print(" 3. 调整服务配置（如需要）")
print()
if __name__ == '__main__':
main()
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