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added image metadata

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This commit is contained in:
deepbeepmeep 2025-07-23 01:47:07 +02:00
parent 4a38beca5b
commit d2843303a2
6 changed files with 59 additions and 30 deletions
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2
defaults/flux_dev.json
View File

@ -12,5 +12,5 @@
},
"prompt": "draw a hat",
"resolution": "1280x720",
"video_length": 1
"batch_size": 1
}

2
defaults/flux_dev_kontext.json
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@ -13,7 +13,7 @@
},
"prompt": "add a hat",
"resolution": "1280x720",
"video_length": 1
"batch_size": 1
}

2
defaults/flux_schnell.json
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@ -13,5 +13,5 @@
"prompt": "draw a hat",
"resolution": "1280x720",
"num_inference_steps": 10,
"video_length": 1
"batch_size": 1
}

2
defaults/t2i.json
View File

@ -6,7 +6,7 @@
"image_outputs": true,
"URLs": "t2v"
},
"video_length": 1,
"batch_size": 1,
"resolution": "1280x720"
}

2
defaults/vace_14B_fusionix_t2i.json
View File

@ -12,5 +12,5 @@
"resolution": "1280x720",
"guidance_scale": 1,
"num_inference_steps": 10,
"video_length": 1
"batch_size": 1
}

79
wgp.py
View File

@ -598,7 +598,7 @@ def add_video_task(**inputs):
"id": current_task_id,
"params": inputs.copy(),
"repeats": inputs["repeat_generation"],
"length": inputs["video_length"],
"length": inputs["video_length"], # !!!
"steps": inputs["num_inference_steps"],
"prompt": inputs["prompt"],
"start_image_labels": start_image_labels,
@ -3141,9 +3141,9 @@ def select_video(state, input_file_list, event_data: gr.EventData):
if not has_video_file_extension(file_name):
img = Image.open(file_name)
width, height = img.size
configs = None
is_image = True
nb_audio_tracks = 0
frames_count = fps = 1
nb_audio_tracks = 0
else:
fps, width, height, frames_count = get_video_info(file_name)
is_image = False
@ -3219,9 +3219,14 @@ def select_video(state, input_file_list, event_data: gr.EventData):
video_length_summary = f"{video_length} frames"
video_window_no = configs.get("window_no", 0)
if video_window_no > 0: video_length_summary +=f", Window no {video_window_no }"
video_length_summary += " ("
if video_length != frames_count: video_length_summary += f"real: {frames_count} frames, "
video_length_summary += f"{frames_count/fps:.1f}s, {round(fps)} fps)"
if is_image:
video_length_summary = configs.get("batch_size", 1)
video_length_label = "Number of Images"
else:
video_length_summary += " ("
video_length_label = "Video Length"
if video_length != frames_count: video_length_summary += f"real: {frames_count} frames, "
video_length_summary += f"{frames_count/fps:.1f}s, {round(fps)} fps)"
video_guidance_scale = configs.get("guidance_scale", None)
video_embedded_guidance_scale = configs.get("embedded_guidance_scale ", None)
if get_model_family(video_model_type) in ["hunyuan", "flux"]:
@ -3255,7 +3260,7 @@ def select_video(state, input_file_list, event_data: gr.EventData):
values += [video_outpainting]
labels += ["Outpainting"]
values += [video_resolution, video_length_summary, video_seed, video_guidance_scale, video_flow_shift, video_num_inference_steps]
labels += [ "Resolution", "Video Length", "Seed", video_guidance_label, "Flow Shift", "Num Inference steps"]
labels += [ "Resolution", video_length_label, "Seed", video_guidance_label, "Flow Shift", "Num Inference steps"]
video_negative_prompt = configs.get("negative_prompt", "")
if len(video_negative_prompt) > 0:
values += [video_negative_prompt]
@ -3914,10 +3919,12 @@ def get_transformer_loras(model_type):
def generate_video(
task,
send_cmd,
image_mode,
prompt,
negative_prompt,
resolution,
video_length,
batch_size,
seed,
force_fps,
num_inference_steps,
@ -4008,9 +4015,8 @@ def generate_video(
model_def = get_model_def(model_type)
is_image = model_def.get("image_outputs", False)
is_image = image_mode == 1
if is_image:
batch_size = video_length
video_length = 1
else:
batch_size = 1
@ -4819,7 +4825,7 @@ def generate_video(
if prompt_enhancer_image_caption_model != None and prompt_enhancer !=None and len(prompt_enhancer)>0:
configs["enhanced_prompt"] = "\n".join(prompts)
configs["generation_time"] = round(end_time-start_time)
if is_image: configs["is_image"] = True
# if is_image: configs["is_image"] = True
metadata_choice = server_config.get("metadata_type","metadata")
video_path = [video_path] if not isinstance(video_path, list) else video_path
for no, path in enumerate(video_path):
@ -5763,7 +5769,7 @@ def prepare_inputs_dict(target, inputs, model_type = None, model_filename = None
if base_model_type in ["t2v"]: unsaved_params = unsaved_params[2:]
pop += unsaved_params
if not vace:
pop += ["frames_positions", "video_guide_outpainting"]
pop += ["frames_positions", "video_guide_outpainting", "control_net_weight", "control_net_weight2"]
if not (diffusion_forcing or ltxv or vace):
pop += ["keep_frames_video_source"]
@ -5772,11 +5778,14 @@ def prepare_inputs_dict(target, inputs, model_type = None, model_filename = None
pop += ["sliding_window_size", "sliding_window_overlap", "sliding_window_overlap_noise", "sliding_window_discard_last_frames"]
if not base_model_type in ["fantasy", "multitalk", "vace_multitalk_14B"]:
pop += ["audio_guidance_scale"]
pop += ["audio_guidance_scale", "speakers_locations"]
if not model_family in ["hunyuan", "flux"]:
pop += ["embedded_guidance_scale"]
if not model_family in ["hunyuan", "wan"]:
pop += ["skip_steps_cache_type", "skip_steps_multiplier", "skip_steps_start_step_perc"]
if model_def.get("no_guidance", False) or ltxv:
pop += ["guidance_scale", "audio_guidance_scale", "embedded_guidance_scale"]
@ -5793,7 +5802,6 @@ def prepare_inputs_dict(target, inputs, model_type = None, model_filename = None
for k in pop:
if k in inputs: inputs.pop(k)
if target == "metadata":
inputs = {k: v for k,v in inputs.items() if v != None }
@ -5969,6 +5977,7 @@ def use_video_settings(state, input_file_list, choice):
file_list, file_settings_list = get_file_list(state, input_file_list)
if choice != None and choice >=0 and len(file_list)>0:
configs = file_settings_list[choice]
file_name= file_list[choice]
if configs == None:
gr.Info("No Settings to Extract")
else:
@ -5978,8 +5987,11 @@ def use_video_settings(state, input_file_list, choice):
defaults.update(configs)
current_model_type = state["model_type"]
prompt = configs.get("prompt", "")
set_model_settings(state, model_type, defaults)
gr.Info(f"Settings Loaded from Video with prompt '{prompt[:100]}'")
set_model_settings(state, model_type, defaults)
if has_image_file_extension(file_name):
gr.Info(f"Settings Loaded from Image with prompt '{prompt[:100]}'")
else:
gr.Info(f"Settings Loaded from Video with prompt '{prompt[:100]}'")
if are_model_types_compatible(model_type,current_model_type):
return gr.update(), str(time.time())
else:
@ -6005,14 +6017,18 @@ def get_settings_from_file(state, file_path, allow_json, merge_with_defaults, sw
tags = file.tags['©cmt'][0]
except:
pass
elif file_path.endswith(".jpg"):
elif has_image_file_extension(file_path):
try:
with Image.open(file_path) as img:
tags = img.info["comment"]
except:
pass
if tags is not None:
configs = json.loads(tags)
try:
configs = json.loads(tags)
if not "WanGP" in configs.get("type", ""): configs = None
except:
configs = None
if configs == None:
return None, False
@ -6072,10 +6088,12 @@ def load_settings_from_file(state, file_path):
def save_inputs(
target,
lset_name,
image_mode,
prompt,
negative_prompt,
resolution,
video_length,
batch_size,
seed,
force_fps,
num_inference_steps,
@ -6382,12 +6400,12 @@ def init_process_queue_if_any(state):
def get_modal_image(image_base64, label):
return "<DIV ALIGN=CENTER><IMG SRC=\"" + image_base64 + "\"><div style='position: absolute; top: 0; left: 0; background: rgba(0,0,0,0.7); color: white; padding: 5px; font-size: 12px;'>" + label + "</div></DIV>"
def get_prompt_labels(multi_prompts_gen_type):
new_line_text = "each new line of prompt will be used for a window" if multi_prompts_gen_type != 0 else "each new line of prompt will generate a new video"
def get_prompt_labels(multi_prompts_gen_type, image_outputs = False):
new_line_text = "each new line of prompt will be used for a window" if multi_prompts_gen_type != 0 else "each new line of prompt will generate " + ("a new image" if image_outputs else "a new video")
return "Prompts (" + new_line_text + ", # lines = comments, ! lines = macros)", "Prompts (" + new_line_text + ", # lines = comments)"
def refresh_prompt_labels(multi_prompts_gen_type):
prompt_label, wizard_prompt_label = get_prompt_labels(multi_prompts_gen_type)
def refresh_prompt_labels(multi_prompts_gen_type, image_mode):
prompt_label, wizard_prompt_label = get_prompt_labels(multi_prompts_gen_type, image_mode == 1)
return gr.update(label=prompt_label), gr.update(label = wizard_prompt_label)
def show_preview_column_modal(state, column_no):
@ -6668,7 +6686,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
image_outputs = model_def.get("image_outputs", False)
sliding_window_enabled = test_any_sliding_window(model_type)
multi_prompts_gen_type_value = ui_defaults.get("multi_prompts_gen_type_value",0)
prompt_label, wizard_prompt_label = get_prompt_labels(multi_prompts_gen_type_value)
prompt_label, wizard_prompt_label = get_prompt_labels(multi_prompts_gen_type_value, image_outputs)
any_video_source = True
fps = get_model_fps(base_model_type)
image_prompt_type_value = ""
@ -6677,6 +6695,15 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
any_end_image = False
any_reference_image = False
# with gr.Tabs(visible = vace or t2v):
# with gr.Tab("Text 2 Video"):
# pass
# with gr.Tab("Text 2 Image"):
# pass
# image_mode = gr.Number(value =ui_defaults.get("image_mode",0), visible = False)
image_mode = gr.Number(value =1 if image_outputs else 0, visible = False)
with gr.Column(visible= test_class_i2v(model_type) or diffusion_forcing or ltxv or recammaster or vace) as image_prompt_column:
if vace:
image_prompt_type_value= ui_defaults.get("image_prompt_type","")
@ -7023,8 +7050,9 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
scale = 5
)
with gr.Row():
batch_size = gr.Slider(1, 16, value=ui_defaults.get("batch_size", 1), step=1, label="Number of Images to Generate", visible = image_outputs)
if image_outputs:
video_length = gr.Slider(1, 16, value=ui_defaults.get("video_length", 1), step=1, label="Number of Images to Generate", visible = True)
video_length = gr.Slider(1, 9999, value=ui_defaults.get("video_length", 1), step=1, label="Number of frames", visible = False)
elif recammaster:
video_length = gr.Slider(5, 193, value=ui_defaults.get("video_length", get_max_frames(81)), step=4, label="Number of frames (16 = 1s), locked", interactive= False, visible = True)
else:
@ -7359,6 +7387,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
video_info_to_video_source_btn = gr.Button("To Video Source", size ="sm", visible = any_video_source)
video_info_eject_video_btn = gr.Button("Eject Video", size ="sm")
with gr.Row(**default_visibility) as image_buttons_row:
video_info_extract_image_settings_btn = gr.Button("Extract Settings", size ="sm")
video_info_to_start_image_btn = gr.Button("To Start Image", size ="sm", visible = any_start_image )
video_info_to_end_image_btn = gr.Button("To End Image", size ="sm", visible = any_end_image)
video_info_to_image_guide_btn = gr.Button("To Control Image", size ="sm", visible = any_control_image )
@ -7454,7 +7483,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
video_prompt_type_image_refs.input(fn=refresh_video_prompt_type_image_refs, inputs = [state, video_prompt_type, video_prompt_type_image_refs], outputs = [video_prompt_type, image_refs, remove_background_images_ref, frames_positions, video_guide_outpainting_col])
video_prompt_type_video_guide.input(fn=refresh_video_prompt_type_video_guide, inputs = [state, video_prompt_type, video_prompt_type_video_guide], outputs = [video_prompt_type, video_guide, image_guide, keep_frames_video_guide, denoising_strength, video_guide_outpainting_col, video_prompt_type_video_mask, video_mask, image_mask, mask_expand])
video_prompt_type_video_mask.input(fn=refresh_video_prompt_type_video_mask, inputs = [state, video_prompt_type, video_prompt_type_video_mask], outputs = [video_prompt_type, video_mask, image_mask, mask_expand])
multi_prompts_gen_type.select(fn=refresh_prompt_labels, inputs=multi_prompts_gen_type, outputs=[prompt, wizard_prompt])
multi_prompts_gen_type.select(fn=refresh_prompt_labels, inputs=[multi_prompts_gen_type, image_mode], outputs=[prompt, wizard_prompt])
video_guide_outpainting_top.input(fn=update_video_guide_outpainting, inputs=[video_guide_outpainting, video_guide_outpainting_top, gr.State(0)], outputs = [video_guide_outpainting], trigger_mode="multiple" )
video_guide_outpainting_bottom.input(fn=update_video_guide_outpainting, inputs=[video_guide_outpainting, video_guide_outpainting_bottom,gr.State(1)], outputs = [video_guide_outpainting], trigger_mode="multiple" )
video_guide_outpainting_left.input(fn=update_video_guide_outpainting, inputs=[video_guide_outpainting, video_guide_outpainting_left,gr.State(2)], outputs = [video_guide_outpainting], trigger_mode="multiple" )
@ -7510,7 +7539,7 @@ def generate_video_tab(update_form = False, state_dict = None, ui_defaults = Non
save_settings_btn.click( fn=validate_wizard_prompt, inputs =[state, wizard_prompt_activated_var, wizard_variables_var, prompt, wizard_prompt, *prompt_vars] , outputs= [prompt]).then(
save_inputs, inputs =[target_settings] + gen_inputs, outputs = [])
video_info_extract_settings_btn.click(fn=validate_wizard_prompt,
gr.on( triggers=[video_info_extract_settings_btn.click, video_info_extract_image_settings_btn.click], fn=validate_wizard_prompt,
inputs= [state, wizard_prompt_activated_var, wizard_variables_var, prompt, wizard_prompt, *prompt_vars] ,
outputs= [prompt]
).then(fn=save_inputs,