basic web-app implementation

eggcount/app.py

@@ -0,0 +1,25 @@
+import dash_bootstrap_components as dbc
+import dash
+
+from eggcount.ui.ui_utils import (
+    get_navbar
+)
+from dash import Dash, html, dcc
+
+app = Dash(
+    __name__,
+    use_pages = True,
+    external_stylesheets=[dbc.themes.BOOTSTRAP]
+)
+
+app.layout = dbc.Container(
+    children = [
+        get_navbar(),
+        dash.page_container
+    ],
+    class_name = "m-0 p-0 w-100 mw-100",
+    id = "content-container"
+)
+
+if __name__ == '__main__':
+    app.run(debug = True)

eggcount/cli.py

@@ -0,0 +1,131 @@
+from eggcount.gradient import (
+    contour_thresh,
+    component_thesh,
+    component_filter_thresh
+)
+from os import PathLike
+from PIL import Image
+from pillow_heif import register_heif_opener
+from typing import Optional
+
+import os
+import cv2
+import numpy as np
+import matplotlib.pyplot as plt
+import fire
+
+register_heif_opener()
+
+def filter_connected_components(
+    img_dir: PathLike,
+    color_thresh: int = 75,
+    avg_area: float = 800,
+    vis: bool = False,
+    save_loc: PathLike = "",
+    kernal_size: tuple[int, int] = (3, 3),
+    max_eggs: Optional[int] = None
+) -> None:
+    # Open image, supports apple HEIC format
+    pil_img = Image.open(img_dir)
+
+    # Convert to standard RGB Image
+    img = np.array(pil_img)
+    res = component_filter_thresh(
+        img,
+        color_thresh = color_thresh,
+        avg_area = avg_area,
+        kernal_size = kernal_size,
+        max_eggs = max_eggs
+    )
+
+    res_vis = res["vis"]
+    res_stats = res["stats"]
+
+    for label, stat in res_stats.items():
+        print(f"{label.replace('-', ' ')}: {stat}")
+
+    if vis:
+        for label, curr_img in res_vis.items():
+            plt.imshow(curr_img)
+            plt.show()
+
+    if save_loc:
+        for label, curr_img in res_vis.items():
+            save_path = os.path.join(save_loc, label + ".png")
+            plt.imsave(save_path, curr_img)
+    
+
+def connected_components(
+    img_dir: PathLike,
+    color_thresh: int = 75,
+    avg_area: float = 800,
+    vis: bool = False,
+    save_loc: PathLike = "",
+    max_eggs: Optional[int] = None
+) -> None:
+    # Open Image
+    pil_img = Image.open(img_dir)
+
+    # Convert to standard RGB Image
+    img = np.array(pil_img)
+
+    res = component_thesh(
+        img,
+        color_thresh = color_thresh,
+        avg_area = avg_area,
+        max_eggs = max_eggs
+    )
+    res_vis = res["vis"]
+    res_stats = res["stats"]
+
+    for label, stat in res_stats.items():
+        print(f"{label.replace('-', ' ')}: {stat}")
+
+    if vis:
+        for label, curr_img in res_vis.items():
+            plt.imshow(curr_img)
+            plt.show()
+
+    if save_loc:
+        for label, curr_img in res_vis.items():
+            save_path = os.path.join(save_loc, label + ".png")
+            plt.imsave(save_path, curr_img)
+
+def contour(
+    img_dir: PathLike,
+    color_thresh: int = 75,
+    avg_area: float = 800,
+    vis: bool = False,
+    save_loc: PathLike = "",
+    kernal_size: tuple[int, int] = (3, 3)
+) -> None:
+    # Open image, supports apple HEIC format
+    pil_img = Image.open(img_dir)
+
+    # Convert to standard RGB Image
+    img = np.array(pil_img)
+    res = contour_thresh(
+        img,
+        color_thresh = color_thresh,
+        avg_area = avg_area,
+        kernal_size = kernal_size
+    )
+
+    res_vis = res["vis"]
+    res_stats = res["stats"]
+
+    for label, stat in res_stats.items():
+        print(f"{label.replace('-', ' ')}: {stat}")
+
+    if vis:
+        for label, curr_img in res_vis.items():
+            plt.imshow(curr_img)
+            plt.show()
+
+    if save_loc:
+        for label, curr_img in res_vis.items():
+            save_path = os.path.join(save_loc, label + ".png")
+            plt.imsave(save_path, curr_img)
+
+if __name__ == "__main__":
+    fire.Fire()

eggcount/demo.py

@@ -1,37 +0,0 @@
-from eggcount.eggcount import (
-    count_eggs_contour_thresh
-)
-from os import PathLike
-from PIL import Image
-from pillow_heif import register_heif_opener
-
-import numpy as np
-import matplotlib.pyplot as plt
-import fire
-
-register_heif_opener()
-
-def demo(
-    img_dir: PathLike,
-    color_thresh: int = 75,
-    avg_area: float = 800
-) -> None:
-    # Open image, suppoorts apple HEIC format
-    pil_img = Image.open(img_dir)
-
-    # Convert to standard RGB Image
-    img = np.array(pil_img)
-
-    num, processed_image = count_eggs_contour_thresh(
-        img,
-        color_thresh = color_thresh,
-        avg_area = avg_area
-    )
-
-    print(num)
-    plt.imshow(processed_image)
-    plt.show()
-
-if __name__ == "__main__":
-    fire.Fire(demo)
-

eggcount/eggcount.py

@@ -1,44 +0,0 @@
-from typing import Tuple
-
-import numpy as np
-import cv2
-import fire
-
-def contour_thresh(
-    img: np.ndarray,
-    color_thresh: int = 75,
-    avg_area: float = 800
-) -> Tuple[int, np.ndarray]:
-    img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
-    bin_mask = cv2.inRange(img_gray, 0, color_thresh)
-
-    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3,3))
-    opening = cv2.morphologyEx(bin_mask, cv2.MORPH_OPEN, kernel, iterations = 1)
-    close = cv2.morphologyEx(opening, cv2.MORPH_CLOSE, kernel, iterations = 2)
-
-    cnts = cv2.findContours(close, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-    cnts = cnts[0] if len(cnts) == 2 else cnts[1]
-    num = 0
-
-    for cnt in cnts:
-        area = cv2.contourArea(cnt)
-
-        if area > avg_area / 2:
-            cv2.drawContours(img, [cnt], -1, (255, 0, 0), 2)
-            curr_num = round(area / avg_area)
-            num += curr_num
-
-            cv2.putText(
-                img,
-                str(curr_num),
-                cnt[0, 0],
-                cv2.FONT_HERSHEY_SIMPLEX,
-                1.5,
-                (0, 0, 255),
-                3
-            )
-
-    return num, img
-
-if __name__ == "__main__":
-    fire.Fire()

eggcount/gradient.py

@@ -0,0 +1,184 @@
+from typing import Tuple, Dict, Optional
+
+import numpy as np
+import cv2
+
+def component_filter_thresh(
+    img: np.ndarray,
+    color_thresh: int = 75,
+    avg_area: float = 800,
+    kernal_size: tuple[int, int] = (3, 3),
+    max_eggs: Optional[int] = None
+) -> Dict:
+    # Clone image, get grayscale, and masc for candidate egg pixels
+    visualization_img = img.copy()
+    img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
+    bin_mask = cv2.inRange(img_gray, 0, color_thresh)
+
+    # Filter pixels not part of a elliptical region
+    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, kernal_size)
+    opening = cv2.morphologyEx(bin_mask, cv2.MORPH_OPEN, kernel, iterations = 1)
+    close =  cv2.morphologyEx(opening, cv2.MORPH_CLOSE, kernel, iterations = 1)
+
+    # Get connected components of filtered image
+    num_labels, labels, stats, centroids = cv2.connectedComponentsWithStats(
+        close,
+    )
+
+    num_eggs = 0
+
+    # Iterate over stats, calculating the number of eggs in each connected component
+    for curr_label, curr_stat in enumerate(stats):
+        left_x = curr_stat[cv2.CC_STAT_LEFT]
+        top_y = curr_stat[cv2.CC_STAT_TOP]
+        area = curr_stat[cv2.CC_STAT_AREA]
+
+        if (area < avg_area / 2) or curr_label == 0:
+            continue
+
+        # Calculate number of eggs
+        curr_num_eggs = round(area / avg_area)
+
+        if max_eggs and (curr_num_eggs > max_eggs):
+            continue
+
+        # Draw border around current component
+        component_mask = (labels == curr_label).astype(np.uint8)
+        contours, _ = cv2.findContours(component_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+        cv2.drawContours(visualization_img, contours, -1, (255, 0, 0), 2)
+
+        # Label current component with number of eggs
+        cv2.putText(
+            visualization_img,
+            str(curr_num_eggs),
+            (left_x, top_y),
+            cv2.FONT_HERSHEY_SIMPLEX,
+            1.5,
+            (0, 0, 255),
+            3
+        )
+
+        num_eggs += curr_num_eggs
+
+    return {
+        "stats": {
+            "Num-Eggs": num_eggs
+        },
+        "vis": {
+            "Egg-Mask": bin_mask.astype(np.uint8),
+            "Ellipse-Filter": close.astype(np.uint8),
+            "Visualization": visualization_img.astype(np.uint8)
+        }
+    }
+
+def component_thesh(
+    img: np.ndarray,
+    color_thresh: int = 75,
+    avg_area: float = 800,
+    max_eggs: Optional[int] = None
+) -> Dict:
+    # Clone image
+    visualization_img = img.copy()
+
+    # Convert to grayscale
+    img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
+
+    # Mask out egg pixels
+    bin_mask = cv2.inRange(img_gray, 0, color_thresh)
+
+    # Get connected components
+    num_labels, labels, stats, centroids = cv2.connectedComponentsWithStats(
+        bin_mask,
+    )
+
+    num_eggs = 0
+
+    # Iterate over stats, calculating the number of eggs in each connected component
+    for curr_label, curr_stat in enumerate(stats):
+        left_x = curr_stat[cv2.CC_STAT_LEFT]
+        top_y = curr_stat[cv2.CC_STAT_TOP]
+        area = curr_stat[cv2.CC_STAT_AREA]
+
+        if (area < avg_area / 2) or curr_label == 0:
+            continue
+
+        # Calculate number of eggs
+        curr_num_eggs = round(area / avg_area)
+
+        if max_eggs and (curr_num_eggs > max_eggs):
+            continue
+
+        # Draw border around current component
+        component_mask = (labels == curr_label).astype(np.uint8)
+        contours, _ = cv2.findContours(component_mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+        cv2.drawContours(visualization_img, contours, -1, (255, 0, 0), 2)
+
+        # Label current component with number of eggs
+        cv2.putText(
+            visualization_img,
+            str(curr_num_eggs),
+            (left_x, top_y),
+            cv2.FONT_HERSHEY_SIMPLEX,
+            1.5,
+            (0, 0, 255),
+            3
+        )
+
+        num_eggs += curr_num_eggs
+
+    return {
+        "stats": {
+            "Num-Eggs": num_eggs
+        },
+        "vis": {
+            "Egg-Mask": bin_mask.astype(np.uint8),
+            "Visualization": visualization_img.astype(np.uint8)
+        }
+    }
+
+def contour_thresh(
+    img: np.ndarray,
+    color_thresh: int = 75,
+    avg_area: float = 800,
+    kernal_size: tuple[int, int] = (3, 3)
+) -> Dict:
+    visualization_img = img.copy()
+    img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
+    bin_mask = cv2.inRange(img_gray, 0, color_thresh)
+
+    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, kernal_size)
+    opening = cv2.morphologyEx(bin_mask, cv2.MORPH_OPEN, kernel, iterations = 1)
+    close = cv2.morphologyEx(opening, cv2.MORPH_CLOSE, kernel, iterations = 2)
+
+    cnts = cv2.findContours(close, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+    cnts = cnts[0] if len(cnts) == 2 else cnts[1]
+    num = 0
+
+    for cnt in cnts:
+        area = cv2.contourArea(cnt)
+
+        if area > avg_area / 2:
+            cv2.drawContours(visualization_img, [cnt], -1, (255, 0, 0), 2)
+            curr_num = round(area / avg_area)
+            num += curr_num
+
+            cv2.putText(
+                visualization_img,
+                str(curr_num),
+                cnt[0, 0],
+                cv2.FONT_HERSHEY_SIMPLEX,
+                1.5,
+                (0, 0, 255),
+                3
+            )
+
+    return {
+        "stats": {
+            "Num-Eggs": num
+        },
+        "vis": {
+            "Egg-Mask": bin_mask.astype(np.uint8),
+            "Ellipse-Filter": close.astype(np.uint8),
+            "Visualization": visualization_img.astype(np.uint8)
+        }
+    }

eggcount/pages/home.py

@@ -0,0 +1,22 @@
+from dash import html, dcc, callback, Input, Output
+
+import dash
+import dash_bootstrap_components as dbc
+
+dash.register_page(__name__, path = "/")
+
+UPLOAD_HEIGHT = "25vh"
+
+layout = dbc.Container(
+    children = dcc.Upload(
+        id = 'upload-data',
+        children = dbc.Container(
+            "Upload Image Here",
+            class_name = "w-100 border border-dark",
+            style = {
+                "height": UPLOAD_HEIGHT
+            }
+        )
+    ),
+    class_name = "text-center mt-3"
+)

eggcount/ui/ui_utils.py

@@ -0,0 +1,19 @@
+import dash_bootstrap_components as dbc
+
+NAVBAR_MIN_HEIGHT = "4rem"
+
+def get_navbar() -> dbc.Nav:
+    return dbc.Nav(
+        children = [
+            dbc.NavItem(
+                dbc.NavLink("Home")
+            ),
+            dbc.NavItem(
+                dbc.NavLink("About")
+            )
+        ],
+        class_name = "bg-dark",
+        style = {
+            "min-height": NAVBAR_MIN_HEIGHT
+        }
+    )