1

litserve_serve.py

@@ -93,14 +93,15 @@ class FluxKleinAPI(ls.LitAPI):
         W = request.get("width", 512)
         H = request.get("height", 512)
         images = []
-        for path in input_image_paths:
-            bucket, *rest = path.split("/", 1)  # 拆分为 ["test", "typical_b/uildi/ng_space_station.png"]
-            object_name = rest[0] if rest else ""
-            image = oss_get_image(oss_client=minio_client, bucket=bucket, object_name=object_name)
-            images.append(image)
+        if input_image_paths:
+            for path in input_image_paths:
+                bucket, *rest = path.split("/", 1)
+                object_name = rest[0] if rest else ""
+                image = oss_get_image(oss_client=minio_client, bucket=bucket, object_name=object_name)
+                images.append(image)
         return {
-            "bucket_name": request.get("bucket_name", None),
-            "object_name": request.get("object_name", None),
+            "bucket_name": request.get("bucket_name", "test"),
+            "object_name": request.get("object_name", f"fida_generate_image/{uuid.uuid4().hex}.png"),
             "images": images,
             "prompt": request.get("prompt", ""),
             "steps": request.get("steps", 4),
@@ -115,15 +116,14 @@ class FluxKleinAPI(ls.LitAPI):
         # 3. 执行推理逻辑
         images = payload.get("images", [])
         prompt = payload.get("prompt", "")
-        W, H = aspect_to_wh(payload["aspect_ratio"], payload["base_long_edge"])
         gen = torch.Generator(device=self.device)
         output = {}
         if images:
             output['im'] = self.pipe(
                 image=images,
                 prompt=prompt,
-                height=H,
-                width=W,
+                height=payload.get("height", 512),
+                width=payload.get("width", 512),
                 guidance_scale=payload["guidance"],
                 num_inference_steps=payload["steps"],
                 generator=gen,
@@ -131,8 +131,8 @@ class FluxKleinAPI(ls.LitAPI):
         else:
             output = self.pipe(
                 prompt=prompt,
-                height=H,
-                width=W,
+                height=payload.get("height", 512),
+                width=payload.get("width", 512),
                 guidance_scale=payload["guidance"],
                 num_inference_steps=payload["steps"],
                 generator=gen,

utils/new_oss_client.py

@@ -61,8 +61,7 @@ def oss_upload_image(oss_client, bucket, object_name, image_bytes):
 
 
 if __name__ == '__main__':
-    url = "fida-test/furniture/sketches/4449a66d-6267-43f7-86a2-1e42bd19ec61.png"
-    read_type = "2"
-    img = oss_get_image(oss_client=minio_client, bucket=url.split('/')[0], object_name=url[url.find('/') + 1:], data_type=read_type)
+    url = "test/fida_generate_image/692932cfecd9499688899812737a369c.png"
+    img = oss_get_image(oss_client=minio_client, bucket=url.split('/')[0], object_name=url[url.find('/') + 1:])
     img.show()
     img.save("result.png")