Update app_lora1.py

app_lora1.py

@@ -2,6 +2,7 @@ import spaces
 import os
 import io
 import torch
+from PIL import Image
 
 import gradio as gr
 import requests
@@ -78,6 +79,7 @@ def pipeline_technology_info(pipe):
 
     return "\n".join(f"• {t}" for t in tech)
 
+
 def pipeline_debug_info(pipe):
     return f"""
 Pipeline Info
@@ -94,6 +96,15 @@ def latent_shape_info(height, width, pipe):
     return f"Expected latent size: ({h}, {w})"
 
 
+# =========================================================
+# PIPELINE FEATURE REGISTRATION HELPER
+# =========================================================
+def register_pipeline_feature(pipe, text: str):
+    if not hasattr(pipe, "_enabled_features"):
+        pipe._enabled_features = []
+    pipe._enabled_features.append(text)
+
+
 # =========================================================
 # DOWNLOAD SCRIPTS (CPU ONLY)
 # =========================================================
@@ -134,8 +145,6 @@ def register_scripts(selected_scripts):
 # =========================================================
 # GPU-ONLY PIPELINE BUILDER (CRITICAL)
 # =========================================================
-
-
 def get_pipeline(script_name):
     if script_name in PIPELINES:
         return PIPELINES[script_name]
@@ -148,6 +157,7 @@ def get_pipeline(script_name):
 
         # Minimal required globals
         "torch": torch,
+        "register_pipeline_feature": register_pipeline_feature,
     }
 
     try:
@@ -168,7 +178,6 @@ def get_pipeline(script_name):
     return PIPELINES[script_name]
 
 
-
 # =========================================================
 # IMAGE GENERATION (LOGIC UNCHANGED)
 # =========================================================
@@ -190,18 +199,27 @@ def generate_image(
         raise RuntimeError("Pipeline not registered")
 
     pipe = get_pipeline(pipeline_name)
-   
-
 
-    
-
-# ✅ Correct, universal, ZeroGPU-safe
+    # ✅ Correct, universal, ZeroGPU-safe
     if not hasattr(pipe, "hf_device_map"):
-      pipe = pipe.to("cuda")
+        pipe = pipe.to("cuda")
+
+    # =========================================================
+    # LOG PIPELINE TECHNOLOGY AND REGISTERED FEATURES
+    # =========================================================
     log("=== PIPELINE TECHNOLOGY ===")
     log(pipeline_technology_info(pipe))
 
+    log("=== PIPELINE FEATURES ===")
+    if hasattr(pipe, "_enabled_features"):
+        for f in pipe._enabled_features:
+            log(f"✔ {f}")
+    else:
+        log("✔ No explicit pipeline features registered")
 
+    # =========================================================
+    # GENERATION LOG
+    # =========================================================
     log("=== NEW GENERATION REQUEST ===")
     log(f"Pipeline: {pipeline_name}")
     log(f"Prompt: {prompt}")
@@ -230,6 +248,13 @@ def generate_image(
         output_type="pil",
     )
 
+    # Resize images to 512x512 for Gradio
+    fixed_images = []
+    for img in result.images:
+        if isinstance(img, Image.Image):
+            img = img.resize((512, 512), Image.BICUBIC)
+        fixed_images.append(img)
+
     try:
         log(pipeline_debug_info(pipe))
         log(latent_shape_info(height, width, pipe))
@@ -238,7 +263,7 @@ def generate_image(
 
     log("Generation complete ✅")
 
-    return result.images, seed, log_buffer.getvalue()
+    return fixed_images, seed, log_buffer.getvalue()
 
 
 # =========================================================
@@ -284,7 +309,12 @@ with gr.Blocks(title="Z-Image Turbo – ZeroGPU") as demo:
 
     run_btn = gr.Button("Generate")
 
-    gallery = gr.Gallery(columns=3)
+    gallery = gr.Gallery(
+        columns=3,
+        height=512,
+        object_fit="contain",
+        label="Output (512×512)"
+    )
     used_seed = gr.Number(label="Used Seed")
     logs = gr.Textbox(lines=12, label="Logs")