fix version

app.py

@@ -1,29 +1,69 @@
-
 import spaces
 import os
-import gradio as gr
 import json
 import torch
+import requests
+import subprocess
+import gradio as gr
+from omegaconf import OmegaConf
+
+# ================== 新增的下载逻辑 ==================
+MODEL_REPO = "pandaphd/generative_photography"
+BRANCH = "main"
+LOCAL_DIR = "ckpts"
+
+
+def download_hf_folder():
+    os.makedirs(LOCAL_DIR, exist_ok=True)
+
+    def get_file_list(path=""):
+        api_url = f"https://huggingface.co/api/spaces/{MODEL_REPO}/tree/{BRANCH}/{path}"
+        try:
+            response = requests.get(api_url, timeout=10)
+            response.raise_for_status()
+            return response.json()
+        except Exception as e:
+            raise RuntimeError(f"Failed to get file list: {str(e)}")
+
+    def download_file(remote_path):
+        url = f"https://huggingface.co/spaces/{MODEL_REPO}/resolve/{BRANCH}/{remote_path}"
+        local_path = os.path.join(LOCAL_DIR, remote_path)
+        os.makedirs(os.path.dirname(local_path), exist_ok=True)
+
+        # 使用 wget 下载（支持断点续传）
+        cmd = [
+            "wget", "-c", "-q", "--show-progress",
+            "-O", local_path, url
+        ]
+        try:
+            subprocess.run(cmd, check=True)
+            print(f"Downloaded: {remote_path}")
+        except subprocess.CalledProcessError:
+            print(f"Failed to download: {remote_path}")
+            raise
+
+    print("Downloading models from Hugging Face...")
+
+    # 递归下载函数
+    def download_recursive(path=""):
+        for item in get_file_list(path):
+            item_path = os.path.join(path, item["path"])
+            if item["type"] == "file":
+                download_file(item_path)
+            elif item["type"] == "directory":
+                download_recursive(item_path)
 
-from huggingface_hub import snapshot_download
-
-from inference_bokehK import load_models as load_bokeh_models, run_inference as run_bokeh_inference, OmegaConf
-from inference_focal_length import load_models as load_focal_models, run_inference as run_focal_inference
-from inference_shutter_speed import load_models as load_shutter_models, run_inference as run_shutter_inference
-from inference_color_temperature import load_models as load_color_models, run_inference as run_color_inference
-
-
-
-
-model_path = "ckpts"
-os.makedirs(model_path, exist_ok=True)
-
-
-print("Downloading models from Hugging Face...")
-snapshot_download(repo_id="pandaphd/generative_photography", local_dir=model_path)
-
+    try:
+        download_recursive()
+        print("All files downloaded successfully!")
+    except Exception as e:
+        print(f"Critical error during download: {str(e)}")
+        exit(1)
 
 
+# ================== 执行下载 ==================
+if not os.path.exists(os.path.join(LOCAL_DIR, "models")):
+    download_hf_folder()
 
 
 torch.manual_seed(42)

app_old.py

@@ -0,0 +1,176 @@
+
+import spaces
+import os
+import gradio as gr
+import json
+import torch
+
+from huggingface_hub import snapshot_download
+
+from inference_bokehK import load_models as load_bokeh_models, run_inference as run_bokeh_inference, OmegaConf
+from inference_focal_length import load_models as load_focal_models, run_inference as run_focal_inference
+from inference_shutter_speed import load_models as load_shutter_models, run_inference as run_shutter_inference
+from inference_color_temperature import load_models as load_color_models, run_inference as run_color_inference
+
+
+
+
+model_path = "ckpts"
+os.makedirs(model_path, exist_ok=True)
+
+
+print("Downloading models from Hugging Face...")
+snapshot_download(repo_id="pandaphd/generative_photography", local_dir=model_path)
+
+
+
+
+
+torch.manual_seed(42)
+
+bokeh_cfg = OmegaConf.load("configs/inference_genphoto/adv3_256_384_genphoto_relora_bokehK.yaml")
+bokeh_pipeline, bokeh_device = load_bokeh_models(bokeh_cfg)
+
+focal_cfg = OmegaConf.load("configs/inference_genphoto/adv3_256_384_genphoto_relora_focal_length.yaml")
+focal_pipeline, focal_device = load_focal_models(focal_cfg)
+
+shutter_cfg = OmegaConf.load("configs/inference_genphoto/adv3_256_384_genphoto_relora_shutter_speed.yaml")
+shutter_pipeline, shutter_device = load_shutter_models(shutter_cfg)
+
+color_cfg = OmegaConf.load("configs/inference_genphoto/adv3_256_384_genphoto_relora_color_temperature.yaml")
+color_pipeline, color_device = load_color_models(color_cfg)
+
+@spaces.GPU(duration=30)
+def generate_bokeh_video(base_scene, bokehK_list):
+    try:
+        torch.manual_seed(42) 
+        if len(json.loads(bokehK_list)) != 5:
+            raise ValueError("Exactly 5 Bokeh K values required")
+        return run_bokeh_inference(
+            pipeline=bokeh_pipeline, tokenizer=bokeh_pipeline.tokenizer,
+            text_encoder=bokeh_pipeline.text_encoder, base_scene=base_scene,
+            bokehK_list=bokehK_list, device=bokeh_device
+        )
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+@spaces.GPU(duration=30)
+def generate_focal_video(base_scene, focal_length_list):
+    try:
+        torch.manual_seed(42)
+        if len(json.loads(focal_length_list)) != 5:
+            raise ValueError("Exactly 5 focal length values required")
+        return run_focal_inference(
+            pipeline=focal_pipeline, tokenizer=focal_pipeline.tokenizer,
+            text_encoder=focal_pipeline.text_encoder, base_scene=base_scene,
+            focal_length_list=focal_length_list, device=focal_device
+        )
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+@spaces.GPU(duration=30)
+def generate_shutter_video(base_scene, shutter_speed_list):
+    try:
+        torch.manual_seed(42)
+        if len(json.loads(shutter_speed_list)) != 5:
+            raise ValueError("Exactly 5 shutter speed values required")
+        return run_shutter_inference(
+            pipeline=shutter_pipeline, tokenizer=shutter_pipeline.tokenizer,
+            text_encoder=shutter_pipeline.text_encoder, base_scene=base_scene,
+            shutter_speed_list=shutter_speed_list, device=shutter_device
+        )
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+
+@spaces.GPU(duration=30)
+def generate_color_video(base_scene, color_temperature_list):
+    try:
+        torch.manual_seed(42)
+        if len(json.loads(color_temperature_list)) != 5:
+            raise ValueError("Exactly 5 color temperature values required")
+        return run_color_inference(
+            pipeline=color_pipeline, tokenizer=color_pipeline.tokenizer,
+            text_encoder=color_pipeline.text_encoder, base_scene=base_scene,
+            color_temperature_list=color_temperature_list, device=color_device
+        )
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+
+
+bokeh_examples = [
+    ["A variety of potted plants are displayed on a window sill, with some of them placed in yellow and white cups. The plants are arranged in different sizes and shapes, creating a visually appealing display.", "[18.0, 14.0, 10.0, 6.0, 2.0]"],
+    ["A colorful backpack with a floral pattern is sitting on a table next to a computer monitor.", "[2.3, 5.8, 10.2, 14.8, 24.9]"]
+]
+
+focal_examples = [
+    ["A small office cubicle with a desk.", "[25.1, 36.1, 47.1, 58.1, 69.1]"],
+    ["A large white couch in a living room.", "[55.0, 46.0, 37.0, 28.0, 25.0]"]
+]
+
+shutter_examples = [
+    ["A brown and orange leather handbag.", "[0.11, 0.22, 0.33, 0.44, 0.55]"],
+    ["A variety of potted plants.", "[0.2, 0.49, 0.69, 0.75, 0.89]"]
+]
+
+color_examples = [
+    ["A blue sky with mountains.", "[5455.0, 5155.0, 5555.0, 6555.0, 7555.0]"],
+    ["A red couch in front of a window.", "[3500.0, 5500.0, 6500.0, 7500.0, 8500.0]"]
+]
+
+
+with gr.Blocks(title="Generative Photography") as demo:
+    gr.Markdown("# **Generative Photography: Scene-Consistent Camera Control for Realistic Text-to-Image Synthesis** ")
+
+    with gr.Tabs():
+        with gr.Tab("BokehK Effect"):
+            gr.Markdown("### Generate Frames with Bokeh Blur Effect")
+            with gr.Row():
+                with gr.Column():
+                    scene_input_bokeh = gr.Textbox(label="Scene Description", placeholder="Describe the scene you want to generate...")
+                    bokeh_input = gr.Textbox(label="Bokeh Blur Values", placeholder="Enter 5 comma-separated values from 1-30, e.g., [2.44, 8.3, 10.1, 17.2, 24.0]")
+                    submit_bokeh = gr.Button("Generate Video")
+                with gr.Column():
+                    video_output_bokeh = gr.Video(label="Generated Video")
+            gr.Examples(bokeh_examples, [scene_input_bokeh, bokeh_input], [video_output_bokeh], generate_bokeh_video)
+            submit_bokeh.click(generate_bokeh_video, [scene_input_bokeh, bokeh_input], [video_output_bokeh])
+
+        with gr.Tab("Focal Length Effect"):
+            gr.Markdown("### Generate Frames with Focal Length Effect")
+            with gr.Row():
+                with gr.Column():
+                    scene_input_focal = gr.Textbox(label="Scene Description", placeholder="Describe the scene you want to generate...")
+                    focal_input = gr.Textbox(label="Focal Length Values", placeholder="Enter 5 comma-separated values from 24-70, e.g., [25.1, 30.2, 33.3, 40.8, 54.0]")
+                    submit_focal = gr.Button("Generate Video")
+                with gr.Column():
+                    video_output_focal = gr.Video(label="Generated Video")
+            gr.Examples(focal_examples, [scene_input_focal, focal_input], [video_output_focal], generate_focal_video)
+            submit_focal.click(generate_focal_video, [scene_input_focal, focal_input], [video_output_focal])
+
+        with gr.Tab("Shutter Speed Effect"):
+            gr.Markdown("### Generate Frames with Shutter Speed Effect")
+            with gr.Row():
+                with gr.Column():
+                    scene_input_shutter = gr.Textbox(label="Scene Description", placeholder="Describe the scene you want to generate...")
+                    shutter_input = gr.Textbox(label="Shutter Speed Values", placeholder="Enter 5 comma-separated values from 0.1-1.0, e.g., [0.15, 0.32, 0.53, 0.62, 0.82]")
+                    submit_shutter = gr.Button("Generate Video")
+                with gr.Column():
+                    video_output_shutter = gr.Video(label="Generated Video")
+            gr.Examples(shutter_examples, [scene_input_shutter, shutter_input], [video_output_shutter], generate_shutter_video)
+            submit_shutter.click(generate_shutter_video, [scene_input_shutter, shutter_input], [video_output_shutter])
+
+        with gr.Tab("Color Temperature Effect"):
+            gr.Markdown("### Generate Frames with Color Temperature Effect")
+            with gr.Row():
+                with gr.Column():
+                    scene_input_color = gr.Textbox(label="Scene Description", placeholder="Describe the scene you want to generate...")
+                    color_input = gr.Textbox(label="Color Temperature Values", placeholder="Enter 5 comma-separated values from 2000-10000, e.g., [3001.3, 4000.2, 4400.34, 5488.23, 8888.82]")
+                    submit_color = gr.Button("Generate Video")
+                with gr.Column():
+                    video_output_color = gr.Video(label="Generated Video")
+            gr.Examples(color_examples, [scene_input_color, color_input], [video_output_color], generate_color_video)
+            submit_color.click(generate_color_video, [scene_input_color, color_input], [video_output_color])
+
+if __name__ == "__main__":
+    demo.launch(share=True)

requirements.txt

@@ -7,7 +7,6 @@ imageio-ffmpeg
 numpy==1.24.4
 transformers==4.39.3
 accelerate==0.30.0
-huggingface_hub==0.25.2
 opencv-python
 gdown
 einops