合并分支
* Merge branch 'main' into feature/modal-cluster-gemini * FIX 修复拼接网格图的异步失效问题 * FIX 修复拼接网格图的异步失效问题 * Merge branch 'main' into feature/modal-cluster-gemini * Merge branch 'main' into feature/modal-cluster-gemini * FIX 调高合成网格图容器配置 * Merge branch 'main' into feature/modal-cluster-gemini * FIX 修复带图片模态推理接口 * PERF 优化Gemini Prompt词 * Merge remote-tracking branch 'origin/main' into feature/modal-cluster-gemini * ADD 增加网格图片创建接口 ADD gemini推理打点增加商品封面模态 PERF gemini打点结果相邻时间线同商品合并 * Merge branch 'main' into feature/modal-cluster-gemini * FIX 429重试机制 * FIX 修复Gemini推理函数入参 * Merge branch 'main' into feature/modal-cluster-gemini * PERF gemini修改参数类型 ADD 增加批量删除Gemini文件接口 * PERF gemini修改prompt * Merge branch 'feature/modal-cluster' into feature/modal-cluster-gemini * PERF gemini修改prompt * 录制HLS时 结果复制到S3挂载点增加一个fallback处理 * Merge branch 'feature/modal-cluster' into feature/modal-cluster-gemini * PERF gemini修改prompt * PERF gemini增加图像模态 * PERF gemini增加图像模态 * fix : TikHub的Logger换为Loguru * fix : 修复直播切分视频接口 * Merge branch 'feature/modal-cluster' into feature/modal-cluster-gemini * PERF tikhub接口增加随机延迟 * Merge remote-tracking branch 'origin/feature/modal-cluster' into feature/modal-cluster * 合并分支 * fix : hls录制缓存读写问题 * FIX 修改冲突 * ADD 增加获取直播间指定商品数量接口 * Merge branch 'feature/modal-cluster' into feature/modal-cluster-gemini * PERF 修改tikhub到aws * fix : 增加s3分片上传接口 * PERF Gemini推理直接从参数列表获取商品列表 ADD Tikhub增加获取置顶|讲解中商品接口 * PERF Gemini推理直接从参数获取商品列表 * Merge branch 'feature/modal-cluster' into feature/modal-cluster-gemini * fix 处理jpg图片的codec_name应为mjpg * Merge branch 'feature/modal-cluster' into feature/modal-cluster-gemini * PERF 优化返回值 * fix 获取媒体metadata的类型报错，modal client升级到1.0.2 * Merge branch 'feature/modal-cluster' into feature/modal-cluster-gemini * PERF 风控后爬虫直接退出避免cookie失效 PERF 分离tikhub api, 使用更低的保持时间以更换IP FIX 修复Dict键不存在报错的bug * fix 一些webhook相关的bug，添加了更详细的接口说明 * 更新直播录制为可跳转时间的hls流接口，用于替代掉腾讯VOD+火山云拉流转推，片段保证每片开头为关键帧，时间精度准确到毫秒级 * ADD 增加直播间商品增量缓存触发器 * Merge branch 'feature/modal-cluster' into feature/modal-cluster-gemini * PERF 调整gemini prompt * - KVCache类改为可拓展，基于环境变量设置KV space - test 环境配置与CF测试环境对齐 * FIX 修复Gemini推理视频切条的问题 PERF 优化视频切条函数性能 * ADD 基本完成gemini视频推理API * ADD 添加内联的tikhub * 对齐预发环境 --------- Merge request URL: https://g-ldyi2063.coding.net/p/dev/d/modalDeploy/git/merge/4799 Co-authored-by: 康宇佳，shuohigh@gmail.com
This commit is contained in:
Coding
parent
8e958b56d1
commit
8d57e593f8
|
|
@ -45,40 +45,8 @@ with downloader_image.imports():
|
||||||
:return: 图片路径
|
:return: 图片路径
|
||||||
"""
|
"""
|
||||||
try:
|
try:
|
||||||
cell_height = image_size + text_height
|
|
||||||
cell_width = image_size
|
|
||||||
# 提取图片路径和文字说明
|
|
||||||
image_paths = []
|
|
||||||
captions = []
|
|
||||||
for info in image_info_list:
|
|
||||||
captions.append(info["title"])
|
|
||||||
if "resize:200" in info["cover"]:
|
|
||||||
info["cover"] = info["cover"].replace("resize:200", f"resize:{image_size}")
|
|
||||||
image_paths.append(info["cover"])
|
|
||||||
|
|
||||||
# 检查输入
|
|
||||||
if len(image_paths) != len(captions):
|
|
||||||
raise ValueError("图片数量与文字说明数量不匹配")
|
|
||||||
|
|
||||||
# 处理图片（包括从网络获取）
|
|
||||||
loaded_images = []
|
|
||||||
for path in image_paths:
|
|
||||||
if path.startswith(('http://', 'https://')):
|
|
||||||
try:
|
|
||||||
response = requests.get(path)
|
|
||||||
response.raise_for_status()
|
|
||||||
img = Image.open(BytesIO(response.content))
|
|
||||||
loaded_images.append(img)
|
|
||||||
except requests.RequestException as e:
|
|
||||||
raise FileNotFoundError(f"无法从网络获取图片: {path}, 错误: {e}")
|
|
||||||
elif os.path.exists(path):
|
|
||||||
img = Image.open(path)
|
|
||||||
loaded_images.append(img)
|
|
||||||
else:
|
|
||||||
raise FileNotFoundError(f"找不到图片文件: {path}")
|
|
||||||
|
|
||||||
# 计算网格大小
|
# 计算网格大小
|
||||||
n = len(image_paths)
|
n = len(image_info_list)
|
||||||
max_cols = min(4, n) # 最大列数为6或图片数量
|
max_cols = min(4, n) # 最大列数为6或图片数量
|
||||||
min_rows = math.ceil(n / max_cols) # 最小行数
|
min_rows = math.ceil(n / max_cols) # 最小行数
|
||||||
|
|
||||||
|
|
@ -100,6 +68,39 @@ with downloader_image.imports():
|
||||||
if best_rows > 4 or best_cols > 4:
|
if best_rows > 4 or best_cols > 4:
|
||||||
raise ValueError(f"图片数量({n})过多，无法在4x4网格内合理展示")
|
raise ValueError(f"图片数量({n})过多，无法在4x4网格内合理展示")
|
||||||
|
|
||||||
|
cell_height = image_size + text_height
|
||||||
|
cell_width = image_size
|
||||||
|
# 提取图片路径和文字说明
|
||||||
|
image_paths = []
|
||||||
|
captions = []
|
||||||
|
for info in image_info_list:
|
||||||
|
captions.append(info["title"])
|
||||||
|
if "resize:200" in info["cover"]:
|
||||||
|
info["cover"] = info["cover"].replace("resize:200", f"resize:{image_size}")
|
||||||
|
image_paths.append(info["cover"])
|
||||||
|
|
||||||
|
# 检查输入
|
||||||
|
if len(image_paths) != len(captions):
|
||||||
|
raise ValueError("图片数量与文字说明数量不匹配")
|
||||||
|
|
||||||
|
# 处理图片（包括从网络获取）
|
||||||
|
loaded_images = []
|
||||||
|
for path in image_paths:
|
||||||
|
if path.startswith(('http://', 'https://')):
|
||||||
|
try:
|
||||||
|
async with httpx.AsyncClient(timeout=60) as client:
|
||||||
|
response = await client.get(path)
|
||||||
|
response.raise_for_status()
|
||||||
|
img = Image.open(BytesIO(response.content))
|
||||||
|
loaded_images.append(img)
|
||||||
|
except requests.RequestException as e:
|
||||||
|
raise FileNotFoundError(f"无法从网络获取图片: {path}, 错误: {e}")
|
||||||
|
elif os.path.exists(path):
|
||||||
|
img = Image.open(path)
|
||||||
|
loaded_images.append(img)
|
||||||
|
else:
|
||||||
|
raise FileNotFoundError(f"找不到图片文件: {path}")
|
||||||
|
|
||||||
# 创建画布
|
# 创建画布
|
||||||
canvas_width = best_cols * (cell_width + separator) - separator
|
canvas_width = best_cols * (cell_width + separator) - separator
|
||||||
canvas_height = best_rows * (cell_height + separator) - separator
|
canvas_height = best_rows * (cell_height + separator) - separator
|
||||||
|
|
|
||||||
Loading…
Reference in New Issue