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import gradio as gr
import cv2
import os
import time
from utils import is_video, process_frame_mock
def sam3d_prediction_fn(file_paths, progress=gr.Progress()):
"""
Processes a list of file paths (images or videos).
Simulates the SAM3D/Rerun logic by iterating through files
and yielding results for a streaming UI.
"""
if not file_paths:
return [], "No files uploaded."
processed_results = []
total_files = len(file_paths)
status_log = ""
# Global frame counter simulation (as mentioned in your thought trace)
global_frame_idx = 0
for i, file_path in enumerate(file_paths):
file_name = os.path.basename(file_path)
status_msg = f"Processing file {i+1}/{total_files}: {file_name}..."
status_log += status_msg + "\n"
# Yield status update immediately
yield processed_results, status_log
# Determine if file is video or image
if is_video(file_path):
cap = cv2.VideoCapture(file_path)
frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
# Process video frames (simulating frame-by-frame logic)
# We'll just process a few frames to keep the demo quick
max_frames_to_preview = 5
current_frame = 0
while cap.isOpened() and current_frame < max_frames_to_preview:
ret, frame = cap.read()
if not ret:
break
# Simulate SAM3D processing on the frame
processed_frame = process_frame_mock(frame, f"Video Frame {global_frame_idx}")
processed_results.append((processed_frame, f"{file_name} - Frame {current_frame}"))
global_frame_idx += 1
current_frame += 1
# Stream updates every frame
yield processed_results, status_log
time.sleep(0.1) # Simulate processing time
cap.release()
status_log += f"Finished video: {file_name}\n"
else:
# Process single image
image = cv2.imread(file_path)
if image is not None:
processed_image = process_frame_mock(image, f"Image {global_frame_idx}")
processed_results.append((processed_image, file_name))
global_frame_idx += 1
# Stream update
yield processed_results, status_log
time.sleep(0.5) # Simulate processing time
status_log += f"Finished image: {file_name}\n"
status_log += "All processing complete."
yield processed_results, status_log
# --- Gradio 6 Application Structure ---
with gr.Blocks() as demo:
# Header with required link
gr.Markdown("# SAM3D Multi-File Processor")
gr.Markdown("[Built with anycoder](https://huggingface.co/spaces/akhaliq/anycoder)")
with gr.Row():
with gr.Column(scale=1):
# UPDATED: Using gr.File with file_count="multiple" as requested
input_files = gr.File(
file_count="multiple",
label="Input Images/Videos",
file_types=["image", "video"]
)
process_btn = gr.Button("Start Processing", variant="primary")
# Log output to see the sequential processing logic
log_output = gr.Textbox(label="Processing Log", lines=10, interactive=False)
with gr.Column(scale=2):
# Gallery to display the streaming results
output_gallery = gr.Gallery(
label="Processed Stream",
columns=3,
height=600,
object_fit="contain"
)
# Event Listener
process_btn.click(
fn=sam3d_prediction_fn,
inputs=[input_files],
outputs=[output_gallery, log_output],
api_visibility="public"
)
# Launch with Gradio 6 parameters
if __name__ == "__main__":
demo.launch(
theme=gr.themes.Soft(),
footer_links=[
{"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"}
]
) |