Upload 10 files

.gitattributes

@@ -33,3 +33,11 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+scene/scene1.jpg filter=lfs diff=lfs merge=lfs -text
+scene/scene2.jpg filter=lfs diff=lfs merge=lfs -text
+scene/scene3.jpg filter=lfs diff=lfs merge=lfs -text
+scene/scene4.jpg filter=lfs diff=lfs merge=lfs -text
+scene/scene5.jpg filter=lfs diff=lfs merge=lfs -text
+scene/scene6.jpg filter=lfs diff=lfs merge=lfs -text
+scene/scene7.jpg filter=lfs diff=lfs merge=lfs -text
+scene/scene8.jpg filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,120 @@
+import gradio as gr
+import cv2
+import numpy as np
+
+# from panorama import stitch_images
+
+
+def process_images(image_files, crop, y_start, y_end, x_start, x_end):
+    if not image_files:
+        return "No images uploaded.", None
+
+    # Extract the first element of each tuple if it's a tuple
+    extracted_images = []
+    for item in image_files:
+        if isinstance(item, tuple):
+            # If item is (img, None), extract 'img' only
+            img = item[0]
+        else:
+            # If for some reason it's not a tuple, assume it's already the image
+            img = item
+
+        # Check if img is not None and is a numpy array
+        if img is not None and isinstance(img, np.ndarray):
+            extracted_images.append(img)
+
+    # If after extraction no valid images found
+    if not extracted_images:
+        return "No valid images found for stitching.", None
+
+    try:
+        # Define crop coordinates
+        if crop:
+            crop_coords = (int(y_start), int(y_end), int(x_start), int(x_end))
+        else:
+            crop_coords = None
+
+        # Initialize OpenCV's Stitcher
+        stitcher = cv2.Stitcher_create()
+
+        # Perform stitching
+        status, panorama = stitcher.stitch(extracted_images)
+
+        if status != cv2.Stitcher_OK:
+            raise RuntimeError(f"Stitching failed with status code {status}.")
+
+        if crop:
+            y_start, y_end, x_start, x_end = crop_coords
+            cropped_panorama = panorama[y_start:y_end, x_start:x_end]
+            return panorama, cropped_panorama
+
+        return panorama, None
+
+    except Exception as e:
+        # Raise a gradio Error to avoid returning image outputs as text
+        raise gr.Error(f"Error during stitching: {str(e)}")
+
+
+# Define Gradio interface using Blocks for better layout control
+with gr.Blocks(title="Creating Panorama using OpenCV", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# Creating Panorama using OpenCV")
+    gr.Markdown("Upload the series of images sequentially and get the perfect Panorama!")
+
+    with gr.Row(equal_height=True):
+        
+        examples = [
+            "./scene/scene1.jpg",
+            "./scene/scene2.jpg",
+            "./scene/scene3.jpg",
+            "./scene/scene4.jpg",
+            "./scene/scene5.jpg",
+            "./scene/scene6.jpg",
+            "./scene/scene7.jpg",
+            "./scene/scene8.jpg",
+        ]
+        with gr.Column():
+            image_upload = gr.Gallery(
+                value=examples,
+                columns=4,
+                label="Upload Images",
+                file_types=["image"],
+                format="jpeg",
+                type="numpy",
+            )
+            crop_checkbox = gr.Checkbox(label="Apply Cropping to Panorama", value=False)
+            with gr.Row():
+                y_start = gr.Number(label="Crop Y Start", value=90, interactive=True)
+                y_end = gr.Number(label="Crop Y End", value=867, interactive=True)
+            with gr.Row():
+                x_start = gr.Number(label="Crop X Start", value=1, interactive=True)
+                x_end = gr.Number(label="Crop X End", value=2000, interactive=True)
+            stitch_button = gr.Button("Stitch Images")
+    with gr.Row():
+        with gr.Column():
+            stitched_output = gr.Image(label="Stitched Panorama")
+            cropped_output = gr.Image(label="Cropped Panorama")
+
+
+    # Disable cropping input fields if checkbox is not selected
+    def toggle_crop_inputs(crop):
+        return gr.update(visible=crop), gr.update(visible=crop), gr.update(visible=crop), gr.update(visible=crop)
+
+    crop_checkbox.change(fn=toggle_crop_inputs, inputs=[crop_checkbox], outputs=[y_start, y_end, x_start, x_end])
+
+    # Define the button click event
+    stitch_button.click(
+        fn=process_images,
+        inputs=[image_upload, crop_checkbox, y_start, y_end, x_start, x_end],
+        outputs=[stitched_output, cropped_output],
+    )
+
+    gr.Markdown(
+        """
+        **Note**:
+        - Ensure that the uploaded images have overlapping regions for successful stitching.
+        - Cropping coordinates should be within the dimensions of the stitched panorama.
+        """
+    )
+
+# Launch the Gradio interface
+demo.launch(show_error=True)

requirements.txt

@@ -0,0 +1,2 @@
+opencv-python==4.10.0.84 
+gradio